Difference between revisions of "Team:Genspace/Measurement"

Line 53: Line 53:
  
 
</div>
 
</div>
<div class="content">
+
<div class="content">
<h2 class="c0"><span class="c8">Results</span></h2>
+
<h2>Part 3. Plasmid Copy Measurement</h2>
  
<p class="c0"><span>A preliminary experiment was run using lysate from 1 million cells per reaction.  Eight replicates were run for each sample type (with or without the reporter).  After excluding outliers caused by edge effects, average C</span><span class="c12">T</span><span> values for six replicates for each sample were compared:</span></p><p class="c0 c2"><span></span></p><p class="c0">
+
<p>A preliminary experiment was run using lysate from 1 million cells per reaction.  Eight replicates were run for each sample type (with or without the reporter).  After excluding outliers caused by edge effects, average CT values for six replicates for each sample were compared:</p>
  
<img src="https://static.igem.org/mediawiki/2016/c/c4/T--genspace--pSB1C3_Preliminary_PCN_Analysis.png" alt="">
+
<img src="https://static.igem.org/mediawiki/2016/c/c4/T--genspace--pSB1C3_Preliminary_PCN_Analysis.png" alt="">
 +
<p>Test:                17.02</p>
 +
<p>Control:        21.48</p>
  
</p><p class="c0 c2"><span></span></p><p class="c0 c13"><span>Test:                17.02</span></p><p class="c0 c13"><span>Control:        21.48</span></p><p class="c0"><span>Assuming a perfect doubling of product for each C</span><span class="c12">T</span><span>, this would indicate 22 times as many copies of the target sequence in the test samples compared to the control, or a PCN of ~21 copies per cell.</span></p><p class="c0 c2"><span></span></p><p class="c0"><span>While this result was an order of magnitude less than the expected value, the consistency among replicates of each sample encouraged us to move forward with absolute quantification experiments.</span></p><p class="c0 c2"><span></span></p><p class="c0">
 
  
  
<div class="sub-content">
+
<div class="sub-content">
</p><p class="c0"><span><b>pSB1C3 absolute quantification run #1</b></span></p><p class="c0"><span>Lysate from 1 million stationary phase cells harboring K909006-pSB1C3 was run against a 3-point standard of 10</span><span class="c1">6</span><span>, 10</span><span class="c1">7</span><span>, and 10</span><span class="c1">8</span><span> copies.</span></p><p class="c0 c2"><span></span></p><p class="c0 c2"><span></span></p><p class="c0">
+
</p><p class="c0"><span><b>pSB1C3 absolute quantification run #1</b><p>Lysate from 1 million stationary phase cells harboring K909006-pSB1C3 was run against a 3-point standard of 106, 107, and 108 copies. Linear regression indicates approximately 18.2 copies of the target sequence for every cell in the reaction, or around 17 plasmid copies per cell.</p><p class="c0">
  
<div class="img-block">
+
<div class="img-block">
<!-- fig1 -->
+
<!-- fig1 -->
<img src="https://static.igem.org/mediawiki/2016/d/db/T--genspace--pSB1C3_Absolute_Quantification_1.png" alt="">
+
<img src="https://static.igem.org/mediawiki/2016/d/db/T--genspace--pSB1C3_Absolute_Quantification_1.png" alt="">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAe4AAAGMCAYAAAAcK0EHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz&#10;AAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmcTuX/x/HXdWbGOvZIEmlxEi20KEtZkhZLVCff9v1L&#10;iqRFIrIU7ahUtHxL0Wnx60uLFqSURBvK0SKKtFiyG5zr98e5x3cwuA333HPPvJ+Ph4e5z33OuT7X&#10;Pcxnrutci7HWIiIiIqnBSXYAIiIiEj8lbhERkRSixC0iIpJClLhFRERSiBK3iIhIClHiFhERSSFK&#10;3CIiIikkPdkBiOQn13VPA6YCTwZBcEOO41cADwZBUDkBZZ4OTAEygyBYH8f5xwCVgiCYug9llgXu&#10;AC4ADgGWAROBe4MgWJbX++YhjgOAVkEQjI29ngJ8EQTB7a7rGuA54ELgT6A/8EAQBFX2Q7nbfYau&#10;64ZAmyAI3t7Xe++h3DuBBkEQXJjIcqRoU4tbippLgAVAJ9d1i+/wXiJXI9qbe78JHJ3XgmLJ8nPg&#10;dOAGwAWuiv09y3Xdw/N67zy4H+iQ43UH4J7Y16cCl8eONQbGsQ/13sGOn2FV4P39dO9cua57GTCQ&#10;xP47ElGLW4oO13WLEbVAbwaeAs4HXk5qULkz+3j9o8Aq4PQgCLbGjv3quu404F3gGaDZPpYRr+3q&#10;EgTBqhwvKwA2CIL3chzblKBy/9xP992J67olgCcAj+iXQpGEUuKWoqQNUBZ4i6jr+mp2SNyxrs6e&#10;sZcvALcGQRC6rptGlBAvAMoBs4FbgiD4Inbd4cCDRK3cEHgj9v7aHe5fE1gI1AuC4LvYsW3d9LGu&#10;5JrACNd1LwiCoIXrugcCI4CzgLWx+HsGQbB6xwq6rluBqOu5Q46kDUAQBNZ13X7Ap67r1gmC4HvX&#10;dRcSdU8/kVt8rutWAR4BWsXq/SswOAiC52LnTwE+Ao4HzgT+BvoHQfBsrKwrYudtDYIgLburHJhH&#10;1E2O67pbiVrhi8jxuMJ13WOBh4BTgBXAyCAIhsTeOwm4D2hI9HPsG6BbEAQzd/EZbusqd103A+gd&#10;i+0gYFbs85y5mzrdEwTBMzt+3jFVYuWdBNwOlN7FeSL7hbrKpSi5BJgeBMEKosTaLJaosh1A9IO6&#10;Wezci4l+EAPcBLQF2hF1wS4AXgVwXbc88AlRa7ExUddvE6KWbW5y60rNPtYR+I0osXSMHRsPbCVK&#10;Um2Aw4i6lXNzAlEi+yy3N4MgmAFsBBrt4vod43uR6HNpDtQh6oIe6bpuzrEAtwNvE30u44EnYu8/&#10;CPjABKKu6pzGAZfFyqoaO3db2a7rVgI+JPosTgSuB3q5rnul67qZsfK+BI4h+lzWEvWiQO6fYU6P&#10;Ef3S1oUoOc8D3o/9grSrOj2+Q523CYJgcRAELYMg+D6390X2NyVuKRJc1y0HnAO8Hjv0f0Qt4ytz&#10;nLYFuDgIgrlBEEwCBhE9IwY4lCjh/RoEwS/ALcAVsQFWlxL9X7o8CILvgyD4OHbfC3fxPHmXXeFB&#10;EKwkStJrgiBY5bpuc6AecFns3l8SJbyzXNetk8stDoj9vWZXZRC1Xg/Yzfs545sA/DsIgnlBEPwM&#10;3AsUA2rnOGdKEARPxz6XPrH3jwuCYB2wAdgUBMFfO9RzE1F3PkEQ/JXLoL1OQBZwXRCZRJRo1wKl&#10;gKFAryAIfgmC4FtgJNHntNNnmPOmsX8HVwM3B0EwKQiCIHbfX4Eb91Sn3XxmIvlGiVuKiouIfviO&#10;BwiCYDlRd+gVOc5ZEgTB7zlezwYOjo3QHglkEj0r/hj4N/BdEASWqCX6dRAEWTmu/YIo8dTdx7iP&#10;Jup6Xem67hrXddcAAdEvHUflcv7y2N/Vd3PPcsSSZhxGAqe4rjvcdd13ge+IWsVpOc75IfuLIAiy&#10;f2HIiPP+u1IH+DYIgi057j02CILXYs+rRwNdXdcdHXt2/x/i+3lWO3bejBz3tcCnbP+9SkSdRPYL&#10;PeOWouKS2N8LXdfNPmYA47puy9jrrTtck50INgdBELiuWwtoDZwNdANudF23IVFLPDeG7RMc5N5N&#10;vrv/h+nAL8AZ7NxS/yOX82cR9RycHLtuO67rnkD0i8AXu4gnPce5BpgEVCPq2p5M1K0c7HBNFjvb&#10;1wF2Wbu6h+u6BwEzgfnAO7HYKgNj4rjvxl3c12H771Ui6iSyX6jFLYWe67o1iJ459yPq7sz+cwJR&#10;1+vVsVOrx55XZ2sELAqCYIPrupcCFwVBMDEIgq5EU6uqxO77PXD8DtPLTiZKgjs+98xOCGVyHNux&#10;Oz1nMv2eKHGuDYLg51h39VaigXI7zXeOdRP7QL/YICxc123suu63ruu2IZquNDvW5Z4dz46xZJdf&#10;H2gBnB0EwYAgCP6PaCQ4xJ/E8jo1agFQLzYokFg97nZd9xXgX0S/TLUKguDhIAg+IJqrHk+5PwKb&#10;2fkZ/6lEvQkiBZ5a3FIUXEr0rHX4jiOxXdf9D3AtUQs0HRjruu4dRAnsTqJFTCAajT7Add3lRD/g&#10;2xAlry+BpcDdwAuu6w4AKhFND3o/CIL5sUFP2YnuD6LnqT1d1+1F9AvElTvEuxaoExsM9X6svFdc&#10;172VqIv8MaJu+192Ud+biR4DTHFd9x7gJ2A68F+ihJYzaX0BXB7rBi/B9vOQlxF77u+67ktEv6wM&#10;i72/4xz4XVkL1HVdt2YQBIvivAbgJaIFWZ5wXfch4IhYvboT/bJxoOu65wJziQbO3QXRlL/YI4tt&#10;n2HO5+uxX8JGAA+7rruOaAR9d6JR4aP2Ij6RpFGLW4qCi4FxuU2fIkqCxYhGhH9HlMimET3bfTAI&#10;glEAselSj8WOzyca5XxBEAQ/BUGwgWg0ejmiLtxXiVZnOz9HOTZ2H0uUqOsQdTt3J/oFIadhRL9s&#10;vBs7vx3Rs+vJsT9LgXNi7+0k9vz+1FgMjxEltzZE09veAMbFWt8QJbwlRKPQnyfqlQhj91kaq+d1&#10;RC3/R4HHgW+Jeit2JWdczxNNuZoXm1oWl9hz5bOJnuN/HSv3niAIXiTqURhFNJ3sm1h818bKzY5r&#10;22eYS0x3Aq/Erp9N9L1oFuvN2PHc3OokklTG2sT+e/Q8ryEwxPf95p7nHU/0g28zsMD3/WsTWriI&#10;7MR13TOJupqnJDsWEdl7CW1xe553G9FvxtndancD/X3fPw0o4XneuYksX0R2FgTBe0raIqkr0V3l&#10;P7L9OsVfAQd4nmeIBsRsTnD5IiIihUpCE7fv++OJBrdk+wEYTvRsrwrRMzgRERGJU36PKh8GNPZ9&#10;f77neTcAD7P9akW50aAQEREpinKddpnfiXs5/1uKcSm7Xy95m6VLlyYsoESpVq1aSsYdL9Uvtal+&#10;qU31S23x1K9atWq7fC+/E/d1wCue520mtg5xPpcvIiKS0hKeuH3fX0SsZe37/nSilaZEREQkD7QA&#10;i4iISApR4hYREUkhStwiIiIpRIlbREQkhShxi4iIpBBt6ykiIinh66+/ZsCAARx66KEArFu3jmrV&#10;qtGnTx/S0rZt3Y61lpEjR7Jw4UKysrIoWbIk3bt356CDDtpjGVlZWQwePJhVq1ZRqlQpevXqRbly&#10;5bY7Z+zYsUyePJnSpUtz0UUXceqppzJ27FhmzpyJMYY1a9awcuVKXnvttW3XjBkzhoULF9K3b999&#10;/hyUuEVEJGXUr19/u+Q3aNAgpk+fzmmnnbbt2MyZM1m+fDkPPPAAANOnT+eJJ55g4MCBe7z/m2++&#10;yWGHHcYVV1zB5MmTefHFF7nxxv8t8Llw4UImT57MyJEjCcOQG2+8kRNOOIF//etf/Otf/wKgd+/e&#10;dO7ceds1n3/+OZ9//jlVqsS9s+1uKXGLiEhK2rx5MytWrKBMmTLbHS9fvjwLFixgypQpNGjQgMaN&#10;G3PKKacA8NFHHzFmzBjKly9P6dKlOfXUU2nduvW2a+fMmbMtATds2JAXX3xxu3svWrSI448/nvT0&#10;KH1Wr16dn376iTp16gAwbdo0ypQpwwknRFvDL1myhLfeeourrrqKt956a7/UW4lbRET2Wvjqc9jZ&#10;0/frPc0JjXEuvGq353z11VfccsstrFixAsdxaNu2LfXr19/uHNd16dmzJxMmTGDEiBFUqVKFG264&#10;gbp16zJy5EhGjx5N6dKl6dWr1073X79+PaVLlwagVKlSrF+/frv3DzvsMF5++WU2bNhAVlYW8+bN&#10;o23bttveHzt27LYegQ0bNjBs2DB69+7NL7/8kpePJFdK3CIikjKyu8pXr17NbbfdRtWqVXc65+ef&#10;f+aQQw7ZlkBnzZpF//79eeaZZyhbtiyZmZkAHHfccTtdW6pUKTZs2ABESTz73Gw1atTgvPPO4447&#10;7qBKlSrUqVNn2zPwRYsWkZmZuW2d8VmzZrFy5UoGDBjAmjVrWL58OWPHjqVnz5779BkocYuIyF5z&#10;LrwK9tA6TqSyZcvSu3dvevTowejRo6lYseK292bPns2iRYvo2bMnxhhq1qxJyZIlqVChAhs3bmTV&#10;qlWUL1+eIAho1Gj7va7q1avHjBkzcF2Xzz//nGOOOWa79//55x/Wr1/P8OHDWbduHbfffju1atXa&#10;Vm7Dhg23ndu0aVOaNm0KRAPrJkyYsK0bfl8ocYuISEqqWbMm559/PiNGjKBfv37bjnfs2JEnn3yS&#10;a6+9lszMTIwx3HXXXQD06NGD3r17U7p0aTZt2rTTPdu3b899991Ht27dyMjIoE+fPgC8+uqrVK9e&#10;nVNPPZXFixfTpUsXMjIy6Ny5M8ZEu2/+9ttv255tJ5KxtsBvd21TcXs3bUuX2lS/1Kb6pbb8qt+o&#10;UaOoUaPGdoPT8sNebOuZ637cWoBFREQkhairXEREiqTrrrsu2SHkiVrcIiIiKUSJW0REJIUocYuI&#10;iKQQJW4REUkIa2H9+q1s2VLgZy+lFCVuERHZr7Zutcybt5rBg7+hXbv3uPjiKUyatJS//87a72WN&#10;Hz9+n+/RtWtX/vjjj72+bvHixfTo0WOfy99bGlUuIiL71bRpf3LFFZPZuvV/Le3p05fRqlV17r+/&#10;IVWqFN9vZY0ZM4YOHTrst/vtrezFV/KTEreIiOw3v/22gc6dp22XtLO9//5vfPppLc4775A83vs3&#10;hg4dSnp6OmEY0qBBA9asWcOwYcO47rrreOCBB1i3bh3Lly+nffv2tGvXjh49enDEEUewcOFC1q9f&#10;T//+/alSpQqjR49m1qxZVK5cmdWrVwPw119/8eijj5KVlcWKFSu4+uqrady4MVdffTXVq1cnIyOD&#10;rl27MmjQIAAqVKiwLbbRo0fz9ddfE4Yhp512Gp06dcpTHeOhxC0iIvvNggX/sHbt5l2+P2LEHM44&#10;oxqZmWl7fe9Zs2ZRp04d/v3vfzNnzhzKlSvHhAkT6N69Oz/88AMtW7akSZMmLF++nB49etCuXTsA&#10;6tSpQ9euXXnmmWf48MMPadCgAXPmzOHJJ59k/fr1XHbZZUDU9e15Hscddxzz5s3j+eefp3HjxmzY&#10;sIErrriCww8/nOHDh9OyZUvOPfdcpkyZwoQJEwCYPHkyjzzyCBUrVmTSpEl5+OTip8QtIiL7zZo1&#10;u07aAH/8sYGNG7fmKXGfc845jB07lttvv53MzEyuueaabe9VqFCB1157jWnTplGqVCm2bNmy7b0j&#10;jjgCgMqVK7Ny5Up+++03XNcFot3AsjcJqVSpEi+++CJvv/02AFu3bt12j0MOiXoJfv31V9q0aQNE&#10;G5JkJ+7evXvz9NNPs3LlSk4++eS9rtve0OA0ERHZb6pUKbnb9489thKZmXlrM06fPp1jjz2Whx56&#10;iNNPP52xY8eSvd+G7/vUrVuX3r1706xZM3Luw7Hjc+iaNWsyf/58INoze9GiRQA8++yztG7dmjvv&#10;vJP69evneo9DDz2UuXPnAmy7x5YtW/joo4/o27cvDz/8MO+++y5//vlnnuoYD7W4RURkv6lduyw1&#10;a2ayaNHaXN+/4Ya6lCiRtzaj67oMGTKEF198EWvtttHg9957L+eccw7Dhw9nypQplC5dmvT0dDZv&#10;3pzr4LEjjjiCk08+mc6dO1OpUqVtz6qbNWvGyJEjefnllznggAO2PfvOeY9LL72UwYMHM3Xq1G17&#10;gaenp1OmTBluuOEGSpQowUknnUSVKlXyVMd4aHewBNHuPalN9Uttql9yBcEaLrnkQ37/ff22Y8ZA&#10;v34ncsklh1Oq1O67yQt6/fbVvu4Opha3iIjsV65bhokTz+b771cxf/5KKlQowfHHV+Kww0pTrJie&#10;0O4rJW4REdnvqlYtTtWqB9K8+YHJDqXQ0a8+IiIiKUSJW0REJIUocYuIiKQQJW4REUkIYy3p69fj&#10;5FgMRfadEreIiOxXZutWSs2bR/nBg6nUrh2VLr6YzEmTKPb33/t036ysLN566629uubbb79l4cKF&#10;+1RuQZPwUeWe5zUEhvi+39zzvLHAgURz0w4FPvN9/+JExyAiIvmn9LRplLniCkxsydA0IGP6dLJa&#10;tWL1/feTlcfFSVasWMHbb7/NueeeG/c177zzDs2bN9+2rGlhkNDE7XnebcBlwFoA3/f/FTteHpgM&#10;3JzI8kVEJH8V/+03ynTuvC1p51Ts/fcp/umnZJ13Xp7uPWbMGBYtWsR//vMfFi5cuG1ls5tuuola&#10;tWoxdOhQli5dSlZWFh07dqRmzZrMnDmTH374gVq1alG5cuV9qltBkegW949AB+DFHY7fA4zwfT9x&#10;i7mKiEi+y1iwALM29+VOAUqOGMGGM85gS2bmXt/70ksvZeHChWRlZdGgQQPatWvHkiVLGDp0KEOH&#10;DmXOnDk8/vjjAMyePZvatWtz8skn06JFi0KTtCHBidv3/fGe59XMeczzvMpAC9TaFhEpdMyaNbt9&#10;3/njD5yNGyEPiTvbzz//zJdffsnUqVOx1rJmzRpKlixJ165deeihh1i/fj1nnHFGnu9f0CVj5bQL&#10;gJd93497kfTYmq0pJ1Xjjpfql9pUv9RWUOu3/uCDd/v+1uOOo1yNGmSUL7/b83KrnzGG9PR0jj76&#10;aOrVq8e5557LihUreO2118jIyOD3339n9OjRZGVl0axZM6688kpKly5N+fLlC9zntS/x5FfizrlQ&#10;+hnAwL25OBUXm9ci+alN9Uttql/yFKtVi2I1a5Ie2ypzRxu6dGHt+vWwfn2u78Ou65eVlcWGDRv4&#10;888/GT9+PC+88ALr16/nyiuvZPPmzSxatIiOHTuSlpbGhRdeyLJly6hZsyZDhw6lePHi1KhRY7/V&#10;c1/sxSYjucqvxJ2zdV0b+DmfyhURkXyUVakSa557jnKXXILz++/bjltjWN+vHxsaNMjzvYsVK8bT&#10;Tz+9y/d79Oix07G2bdvStm3bPJdZECU8cfu+vwholOP1MYkuU0REkmeD67J14kSKff89afPnYytU&#10;YPPxx7PpsMMIixVLdngpT7uDiYjIfpdVtSpZVatC8+bJDqXQ0cppIiIiKUSJW0REJIWkROK24c4r&#10;8IiIiBRFKZG4w8G3Yn/8LtlhiIiIJF1KJG4W/0Q4tBfhqIewK/ZtdxkREZFUlhKJ2+l1P9Q8Ajvz&#10;I8K+XQjf8rGbs5IdloiISL5LicRtDj8Kp/eDmCtuguIlsP83hvDurtgvP8PauFdOFRERSXkpkbgB&#10;jOPgNGmFM+hJzJnnwcq/CUfeR/jI3dgli5MdnoiISL5ImcSdzZQqjXPh1Tj9R0C9E+D7bwgHdCMc&#10;+zR23a63khMRESkMUi5xZzNVq5PWvR/OTX3hgKrYyRMJ+/ybcOo7mj4mIiKFVsom7mzm2JNw7hmB&#10;ueBK2LIF+9JIwoG3YBfMTXZoIiIi+13KJ24Ak56B07pj9Py7UUv4bSHhA70Jn7ofu/yvZIcnIiKy&#10;3xSKxJ3NlKuAc1V3nN4PQq3a2FmfEN7dhfC/Y7FZm5IdnoiIyD4rVIk7m6lVG6fX/ZirboaSpbET&#10;xhL2vQE76xNNHxMRkZRWKBM3xKaPNWqBM2gk5qzzYfVKwqfuJ3yoD/a3hckOT0REJE8KbeLOZkqU&#10;wjn/Cpx7HoPjToZgDuGAHoQvjcSuXZ3s8ERERPZKoU/c2UyVaqTd2Aene384sBp26juEd3UmnDwR&#10;u1XTx0REJDUUmcSdzdRrgNNvOMa7BmyIHfs04cCbsd9/k+zQRERE9qjIJW4Ak56O06p9NH2s6Zmw&#10;dDHhw33ZOvI+7F/Lkh2eiIjILhXJxJ3NlC2Pc/mNOHc9BEfUgS8/I7y7K+H/jcFu2pjs8ERERHZS&#10;pBN3NlPzCJzbh2Cu7QmZZbFv+YR9byD8/CNNHxMRkQJFiTvGGIPT8HScgU9gzvFgzT/Y0Q8R3n8n&#10;dvFPyQ5PREQEUOLeiSlREqfDpTgDHof6p8CP3xEOuoXwhcewa/5JdngiIlLEKXHvgqlclbQbeuPc&#10;MhAOOgT78XvR9LEP3sRu2ZLs8EREpIhS4t4DU+c4nLuHYTpdDwbsK88QDuiOnfdVskMTEZEiSIk7&#10;DiYtDadlG5xBT2FOPwuWLSF8tB9bHxuE/fP3ZIcnIiJFSHqyA0glpkxZzKU3YE8/m3Dc0/DNTMJ5&#10;X2Jatcec42FKlEx2iCIiUsipxZ0H5pBaOLfei7n+dihbHvvO64R9uhB+NgUbhnt3L2P2vvwc1+Tl&#10;ehERSV1qceeRMQZzUhPssSdhJ72OffcN7LOPYKe+jdPpeqhWbZfXbt5sWbBgDZMnL2Hu3BXUq1eR&#10;Fi0OpnbtMmRk5J6Ic16zatUmGjY8kHnzVjJ//sq4rhcRkcLBpMACI3bp0qXJjmGP7PI/sa8+h509&#10;HYDSrdqyofUFmHIVtjtv82bLhAm/0q3bJ+T86I2B4cOb0LbtITsl35zX1K1bkTZtajJ06FdxX58I&#10;1apVIxW+L3ml+qU21S+1qX7ROUCuP8zVVb6fmEpVcDrfgXPrYKh+KOven0DYpzPhpPHYLZu3nbdg&#10;wZqdkjaAtdCt2ycsWLBmp3vnvObCCw/fKWnv6XoRESk8lLj3M+Meg9PnESrc0AvS0rGvPUfYvxt2&#10;ziwAJk9eslPSzWYtTJmyZKfj2ddUq1aKxYvX7vX1IiJSeCT8GbfneQ2BIb7vN/c8rzIwCigPpAGX&#10;+76/MNEx5DeTlkbmuRfwT+1jsG++jP3oHcLhAzDHnMifc+vv9tq5c1dijNm2RroxhrlzVwBQtWqU&#10;uPfmehERKVwS2uL2PO82okRdPHbofmCM7/vNgL7AUYksP9lM6TI4F/8b5+5hcNSx2Dmz6Muz9D7q&#10;azLTN+d6Tb16FbZLutZa6tWrCMCyZeupUSNzt2XueL2IiBQuie4q/xHokON1Y6C653nvAxcDUxNc&#10;foFgDq6Jc8tAnC53srVMRTofNp+pp7/FhdV/xvC/JGsMNG9+8E7Xt2hxMMbA0qVR4t7VDLBdXS8i&#10;IoVHQhO37/vjgZwLex8KrPB9vxXwK9ArkeUXJMYYTINTSR/wON8f2YbMtM08dOxM3mz0PvXL/40x&#10;MGJEU2rXLrPTtbVrl2H48CYYA6+++hN33FF/p+S9u+tFRKTwyO953MuBCbGvJwCD8rn8pMsoXQK3&#10;x3X8PLsV9vXnOJ6vebPRB/xTpwllmpTMdSpXRoahbdtDcN02TJmyhJUrN/Hss8357ruVzJ+/inr1&#10;KtC8ueZxi4gUBfmduD8GzgFeAk4D5sVzUbXdLGZSkO0u7po1DyY871Q2zv2S1aMeodz3n2AGzCbz&#10;omso0+FiTEaxXK6Bli1rE4YhjhN1lmR/nf06P6Xq9yVeql9qU/1Sm+q3a/mduG8FRnue1wX4h+g5&#10;9x6l4kT8uBcQOKAa9o4hmE8+wI5/kX/+8xj/vP0ajncNHHdygV3SVAskpDbVL7WpfqltLxZgyVXC&#10;E7fv+4uARrGvFwNnJrrMVGOcNMxprbEnNsZOGIed8hbh44Ph6Po4na7FHHRIskMUEZECQguwFCCm&#10;VCbORdfi9BsOR9eH774ivKcb4Sujset3P39bRESKBiXuAsgcdAjOzf1xut4FFStjP/hvtPvYtEnY&#10;cGuywxMRkSRS4i6gjDGY4xvi3PM4puPlkLUJ++LjhIN7Yn/4LtnhiYhIkihxF3AmIwPn7AtwBo3E&#10;nNIcFv9MeH8vwlEPYlf8nezwREQknylxpwhTvhLONT1wet0Phx6JnTmNsG8XwomvYLM2JTs8ERHJ&#10;J0rcKcYcfhTOnQ9gruwGJUpi33yJ8O6u2C8/1RrlIiJFgBJ3CjKOg9P4DJxBT2Jad4BVKwhHDiF8&#10;uC/2t1+SHZ6IiCSQEncKMyVL4VxwFU7/EXDMiTD/W8IBNxO+/BR23ZpkhyciIgmgxF0ImKoHk9bt&#10;bpxud0OVg6IFXPp0Jpz6tqaPiYgUMkrchYg55kSc/sMxF1wFW7ZgX3qScGAPbDA32aGJiMh+osRd&#10;yJj0DJzWHaLn341bwm+/ED7Ym/DJodjlfyY7PBER2UdK3IWUKVcB58ruOL0fgsNc7OzphH1vIPzv&#10;y9hNmj4mIpKqlLgLOVPrSJw7hmKu6QGlMrETxhHe3YXwi080fUxEJAUpcRcBxnFwTmkerb529gWw&#10;ehX26fsJH+yNXfxzssMTEZG9oMRdhJgSJXE6Xo5zz+Nw3MmwYB7hoFsIxzyBXbM62eGJiEgclLiL&#10;IFPlINJu7INz8z1Q9WDsR+8S9vk34YcTsVs1fUxEpCBT4i7CTN36OHcPw1x0DViw454mHNAd+/03&#10;yQ5NRER2QYm7iDPp6ThntMcZ/CSm6Znw+6+ED/dl6xP3Yv9aluzwRERkB0rcAoApUw7n8htx7noY&#10;jjgavppBeHdXwvFjsBs3JDs8ERGJUeKW7Ziah+Pcfh/muluhTDns2340/3vGVE0fExEpAJS4ZSfG&#10;GJyTT8MZ+ASmzUWwdjX2mYcJ7++FXfRTssMTESnSlLhll0zxEjjtL8EZ+AQ0aAQ/fk84+BbCFx5j&#10;66oVyQ5PRKRIUuKWPTIHHEhal144twyEajWwH7/H79d3JHz/TeyWLckOT0SkSFHilriZOsfh9H0U&#10;86/rMcbB+s8Q3tMNO/fLZIcmIlJkKHHLXjFpaTgt2lB11BuYZmfDH0sJh/Vn62ODsH8uTXZ4IiKF&#10;XnqyA5BKITMbAAAgAElEQVTUlFa2PM4lXbCnn0U4bjR8M5Nw7peYM9ph2niYEqWSHaKISKGkFrfs&#10;E1O9Fk7PQTid74ByFbCT3iDs04Xw0w+xYZjs8ERECh0lbtlnxhjMCY2j6WPtLoYN67DPDSMccjt2&#10;4YJkhyciUqgocct+Y4oVx2nbCWfASMxJTWHhAsJ7byV8bhj2n5XJDk9EpFBQ4pb9zlSqjHP9bTi3&#10;3gvVa2E//ZCwT2fCSW9gt2xOdngiIilNiVsSxrj1cPo+jLmkC6SnY197nrDfTdhvv0h2aCIiKUuJ&#10;WxLKOGk4zc7GGfQUpmVb+HsZ4YiBbB12D3bZb8kOT0Qk5ewxcXue1yA/ApHCzZTOxOl0Hc7dw6HO&#10;cTB3NmH/mwj9Z7Dr1yU7PBGRlBFPi/ulhEchRYY5uAZOjwE4N/SGCgdg338zev798XuaPiYiEod4&#10;FmD51vO8i4FPgLXZB33fj2uXCc/zGgJDfN9v7nne8cBEIHuO0Ejf91/dy5glxRljoP4pOPUaYN/7&#10;P+zbr2JfeAz70bs4na7DHFEn2SGKiBRY8STu9sCFOxyzQNqeLvQ87zbgMv6X8E8AHvJ9/5G9CVIK&#10;J5NRDHOuh23UEvv689jPPyIcegfmlGaY86/AlK+U7BBFRAqcPSZu3/dL7MP9fwQ6AC/GXp8A1PY8&#10;7zzgB6C77/t6wFnEmQqVMNf2xDY7m3DsKOyMqdivZmDOuRDTqj0mo1iyQxQRKTD2mLg9z3OAW4B6&#10;wE3AjcD9vu9v3dO1vu+P9zyvZo5DnwOjfN//yvO83kB/4La8BC6FjzniaJy7HsRO/xA7/sXozyfv&#10;41x4NRzfMOpiFxEp4uIZnPYAcCzQMHb+WUBeu7r/z/f9r2JfjweOz+N9pJAyThpO0zNxBj2JadUe&#10;VvxF+MS9hI/2wy5dnOzwRESSLp5n3C2BBsBs3/f/8TzvTODrPJY3yfO8G33fnxW77+x4LqpWrVoe&#10;i0uuVI07Xgmv38192Xz+Zawa9TAbZ39KeE93MttcSLmLr8cpUzaxZaPvX6pT/VKb6rdr8STuzb7v&#10;h57nAeD7/ibP87bksbwuwAjP87KAZcD18Vy0dGnq7fNcrVq1lIw7XvlWv7Ri2H/fgfPtLEJ/NGv/&#10;O461k9/GnHcppmkrjLPHMZJ5ou9falP9Upvqt/vEHk/inut5XlcgzfM8l+h5d9wtbt/3FwGNYl9/&#10;BTSJ91oRiE0fO+4knKOPx374X+xEHzvmCexH7+B0uh5Tu+4ur7PW5nO0IiKJFU/i7k70TPtAYDow&#10;CeiWyKBEcmMyMjBnnY89pTn2jRewn00mfOBOzElNMRdcialYGbN5MyUWLKDY5Mmkz53Llnr1yGrR&#10;go21a2MzMpJdBRGRfRbPdLDVwDX5EItIXEz5ipirb46mj40bhf3iY+w3n+Oc2ZHMrHTK9LgFE2tp&#10;F584kVJDh7J2+HDWtm2r5C0iKS+e6WBVgGFAK2Az8DbQ0/f9VQmOTWS3zGEuTq/7sTOmYN94gXDi&#10;ONau30T6geUouWwV2ZPHjLVkduvGFtdlQ93cu9VFRFJFPNPBRgE/AycDTYGVwFOJDEokXsZxcBq1&#10;xBk4khKVD2VriQyWNzicv04+kqwy/1s7yFhLsSlTkhipiMj+Ec8z7kN932+f4/WtnufNSVRAInnh&#10;lCpN2eWbKD/tO1bVqc7GA8vzR5OjyVz8F2UXLCVt81bS587VgDURSXnxtLiXep5XK/uF53nVgd8T&#10;F5LI3rPWsqVePTLWb6Ly7J84YOYPpK/bxNqaVVh2ej3W1KzM5rpHK2mLSMrbZYvb87wJRJuJVAa+&#10;9jzvA2Ar0Bz4Nn/CE4lfVosWlBo6FGMtJf9eTYmPv2PtoZX554hqrKpbA2fpXJj/LeaoY5MdqohI&#10;nu2uq/y1XRx/KxGBiOyrjbVrs3b4cDK7dcNYi7GWMgv/pOTSlSy/4nyylvwID/WBExrhXHg1plKV&#10;ZIcsIrLXdpm4fd//T87XnueVSnw4InlnMzJY27YtW1yXYlOm/G8ed/PmhLVr4yz5hXDcKJj9KeG3&#10;szCtO2DOugBTvHiyQxcRiVs808F6AIOB7J9uhjj34xbJbzYjgw1167Khbt2dBqKZQ4/EuWMo9vOP&#10;ov2/J76Cnf5htHjLSU21+5iIpIR4BqfdApwClI39KRP7W6RAy20gmjEG55RmOANHYs65ENaswo56&#10;kPCBO7GLf0pClCIieyee6WA/+L6vwWhSqJgSJTEdLsM2aUXoPwtfzyAcdAum6ZmY8y4FCvfORCKS&#10;uuJJ3I95nvcK8B7RymkA+L7/QsKiEsknpnJV0rr2xn73dbR86rRJ2FmfsObSztj6jTHp8fwXERHJ&#10;P/H8VOpKtMFIzsFpFlDilkLDHH08zt3DsB+9g/3vy6x6+iE4yMfpdC3m6PrJDk9EZJt4EncN3/eP&#10;THgkIklm0tMxLdtiTz6Nku+PZ9274wkf6QfHN8TxrsFUrprsEEVE4hqc9ovneXrgJ0WGKVOOijf2&#10;xunzCBx5NHz9OeHdNxC+8QJ244ZkhyciRVw8Le4NwFzP874ANmUf9H2/XcKiEikATI3DcG67Dzvr&#10;E+xrz2HfeQ372WTM+VdgGjbT9DERSYp4EvfrsT8iRY4xBnNSU+yxJ2PffR076Q3sM49gp76D0+k6&#10;zKF6iiQi+WuPiXvHFdREiiJTvDim/cXYxi0JX3suWn3t3lsxjVpiOl6GKVsh2SGKSBERz8ppa4hG&#10;kW/H930twiJFjjngQNI698LO/zaaPjb9A+yXn2LaXIRp0QaTnpHsEEWkkIunq7xejq+LAR2JdgkT&#10;KbLMUcfi9H00mvf95kvYV5/Dfvwejnct5pgTkh2eiBRi8XSVL9rh0FDP8z4HHkxMSCKpwaSlYZqf&#10;gz2pCfa/L2Onvks4/B445kSci67FHKjJGCKy/+31slCe5x1FtCCLiAAmsyzm4s7Y086Kdh+bM4vw&#10;u68xZ7TFnHsRpqQ21hOR/Wdvn3Ebou7y2xMZlEgqMtUPxek5CL78jPDVZ7GTxmNnTMV0uBxzanOM&#10;E8+yCSIiu7e3z7gtsMr3/dUJikckpRlj4IRGOMecgH1vfDT3+/loKVWn03WYw9xkhygiKW6XTQDP&#10;82p4nleDKFln/wEoHzsuIrtgihXHadMp2j70pKawcAHhfbcRPvsIdtWK3K/Rgi4iEofdtbjnESXr&#10;nD9NLFCSKOGnJTAukULBVKyMuf42bLNzCMc9jf1sCvbLGZhzPcwZ7XCAEgsWUGzyZNLnzmVLvXpk&#10;tWjBxtq1sRmaWiYiO9tl4vZ9v0zO157nGaA3cGvsj4jEydSui9PnYewn72PHj8G+8R/sx5MoeUhd&#10;yg1+AMdGHVrFJ06k1NChrB0+nLVt2yp5i8hO4hpV7nnewcAYoAzQ0Pf9BQmNSqQQMk4a5rSzsCc0&#10;wU4Yi538Fuv+WsbWEw+n/He/krEu2grAWEtmt25scV021K2b5KhFpKDZ4zBXz/M6At8As4FTlbRF&#10;9o0pnYnT6TrKHdmQ4n+tZmPlcixrWpeVdaoTpkf/JY21FJsyJcmRikhBtMsWt+d5JYFhwLlAJ9/3&#10;P8i3qEQKOWMMxX/8hTJf/MDGKuVYWecQ1tY6kPXVKlIuWELp35aTPncuxhis3WnFYREpwnbXVf4l&#10;UJMoeR/red6xOd/0ff/hRAYmUphZa9lSrx7FJ06k5J//UOLv1aypdSCrD6/KymMPZW3NypSodXCu&#10;SVvJXKRo213i/hyYAVSN/clJPzVE9lFWixaUGjoUYy0mtJT9aRmlflvOP0cdzPqDK7H5xy8wox7C&#10;nH8FTplyGn0uIsDuR5VfmY9xiBQ5G2vXZu3w4WR264aJtaDTN22m4reLcC64nLVL5mNnfoT9egbF&#10;ah5NuceexdkaAhp9LlKU7fVa5XvL87yGwBDf95vnOHYxcKPv+40SXb5IQWUzMljbti1bXJdiU6b8&#10;ryXdvDkba9fGSUvDfvohvPocG3/4imVNj6b8979R8o9VGDT6XKSoSmji9jzvNuAyYG2OY/WBqxNZ&#10;rkiqsBkZbKhblw116+707NoApkkrysyaw9YJ41hz6IEsP+Fwiv+9mgrf/UrG2o3bRp8rcYsUHYne&#10;9eBHoEP2C8/zKgGDgO4JLlck5exqIFqx7wPKz19C1Y/nUeLPf9h0QFmWNTmalUcfQpietm30uYgU&#10;DfHM4/7S87xrPc/b670Jfd8fD2yJ3ccBRgO3AOvYfilVEclF9uhzgIx1m6g860cO+OIH0jdsYu2h&#10;Vfi9WT3WVi1HuHVLkiMVkfxi9jStxPO8RsC/gTOB14GRvu/Pi7cAz/NqAmOBbsBzwF9E653XAZ71&#10;ff+WPdxCI9ilSFs/bRolmzXbNoANwBrDmkOrsPrIg7DpaWTUqk35zrdSol6DJEYqIvtZrg3cPSbu&#10;bJ7nlQcuBnoCS4Hhvu+/Gsd1NYFxvu+fusOxsXEOTrNLly6NK8aCpFq1aqRi3PFS/fKP2byZzAkT&#10;tht9DlHyXv3gUNas+xM7I1plzZzYBHPBVZhKlXd7z4JUv0RQ/VKb6hedwy4Sd7xrlZcnGmR2DfAP&#10;4AOXe57X1vf9y+O4hVrNInm0x9HnGRnYFucSjn0aO+sT7LczMa3Px5zVEVOseLLDF5H9bI+J2/O8&#10;l4BzgIlAF9/3P4sdHwn8uafrfd9fBDTa0zGRgizZq5XtdvS5MVCrNk6v++Hzjwhffz7axGT6BzgX&#10;XgUnNNbgNZFCJJ4W9zzgZt/3/8p50Pf9LZ7nNU5MWCLJt3mzZcGCNUyevIS5c1dQr15FWrQ4mNq1&#10;y5CRkbxEaK3dLrZVqzbRsOGBzJu3kvnzi1G/Tg86HjmTil+/S/jU/eAeg9PpWkz1WkmLWUT2n7ie&#10;cXuedw7QGtgKTPB9Pz+3LdIz7gKosNevfPlKPPvsV3Tr9gk5/4sYA8OHN6Ft20OSlrw3b7ZMmPAr&#10;3bp9Qt26FWnTpiZDh361U5zP3OfScuXbmDlfgHEwp7fGtL8Ek1m20H//VL/Upvrt/hl3PNPB+gEP&#10;ET3bXg885Xlet72OVCSFzJq1ZKekDWAtdOv2CQsWrElOYMCCBWu2xXbhhYfvlLQhivOaOwOClt1x&#10;uveHA6thp75DeFdnwskTsZo+JpKy4lmA5TLgFN/37/Z9vw/QEOiS2LBEkmvSpEU7JcNs1sKUKUvy&#10;N6AcJk9egrVQrVopFi9eu8c4Tb0GOP2GY7xrwIbYsU/zx02XYL//Jn8DF5H9Ip7EvRzI2bxYRY4l&#10;TEUKG2MM3377927PmTt3ZVIGfBljmDt3BQBVq0aJe3ey4zTp6Tit2uMMehLT9Ew2L/6Z8OG+bB15&#10;H/avZfkRuojsJ/Ek7lnAm57ntfE87yzgRWCx53kdPc/rmNjwRPKftZZjjz1gt+fUq1chKaPMrbXU&#10;q1cRgGXL1lOjRuZuz98xTlO2PM7lN3LgIy/AEXXgy88I7+5K+H9jsJs2JjR2Edk/4kncRwOZRAuv&#10;3AEcDFQEbgJuTFxoIsnTunVNdtWgNgaaNz84fwPKoUWLgzEGli6NEnde4ix2ZB2c24dgru0JmWWx&#10;b/mEfW8g/PyjpE57E5E92+N0sOztOD3PSweM7/ubEx6VSJKdeOLBDB/eJNdR5SNGNKV27TJJi612&#10;7TLbYnv11Z+44476uY4q31OcxhhMw9Oxx52Mfed17HvjsaMfwk59B+df12FqHJ4PtRGRvRXPWuVV&#10;gP8ALYgS/UfApb7v59dYfU0HK4CKQv0WLVrCggVrmDJlCXPnrqRevQo0b578edzwvznmU6YsYeXK&#10;aB73d9+tZP78VXHFmdv3z/61jPDVZ+GrGWAMpkkrTIfLMGXK5UeV9qui8O9T9Utd+bHk6WPADOBf&#10;QBrRZiEjgfZ7E6hIqsnIMNStW5a6dcsmfeW0HeUW25lnHrRPcZrKVUm7oTf2+28Ix43CfvwedtZ0&#10;TLtOmGbnYtLjWiFZRBIsnv+JtX3f93K87ud5Xty7g4kUBgUpae8oZ2z7I05T5zicu4dhp76D/e9L&#10;2FeewU57D+eiazF16+/z/UVk38QzOC3D87wS2S9i+3IX3J9iIrLPTFoaTss2OIOewpx+FixbQvho&#10;P7Y+Ngj75+/JDk+kSIunxT0O+MDzvOdir68CXktcSCJSUJgyZTGX3oA9/WzCcU/DNzMJ532JadUe&#10;c46HKVEy2SGKFDl7bHH7vj8QeAY4EzgLeB64J7FhiUhBYg6phXPrvZjrb4ey5bHvvE7YpwvhZ1Ow&#10;YZjs8ESKlN22uD3PywCK+77/HPCc53nHAPN931dXuUgRY4zBnNQEe+xJ2EmvY999A/vsI9ipb+N0&#10;uh5T68hkhyhSJOyyxe15XnWiLT3b5DjcB5jjeV61RAcmIgWTKV4cp93FOAOfwJzQGH4OCO/tSfj8&#10;MOw/K5Mdnkiht7uu8geAZ33fH5d9wPf9i4AxwP2JDkxECjZTqQpO5ztwbh0M1Q/FTv+QsE9nwknj&#10;sVu0TpNIouwucdfzfX9ILsfvBRokKB4RSTHGPQanzyOYSzpDWjr2tecI+3fDzpmV7NBECqXdJe6s&#10;3A76vh8C2o1ARLYxaWk4zc7BGfwkpvm58NfvhMMHsHX4AOyy5G2BKlIY7S5xr/Y8r9aOBz3POxzY&#10;kriQRCRVmdJlcC7+N87dw+CoY2HOLML+NxG++hx2w/pkhydSKOxuVPlDwATP87oBnxIl+VOAYUTd&#10;5SIiuTIH18S5ZSB8NYPQfybawGTGFEzHyzGntsA48az9JCK52eX/Ht/3JxIl6NHAOmAN8Dhwr+/7&#10;Y/MnPBFJVcYYTINTcQY8jml/CWzcgH1+OOF9t2F/mp/s8ERS1m7ncfu+/zLwsud5FYHQ9/1V+ROW&#10;iBQWplhxTJuLsI1aYl9/HjtzGuGQ2zGnNMecfzmmfKVkhyiSUuLa7sf3/RWJDkRECjdT8QDMdbdi&#10;m51DOO5p7Iwp2K8+w5zrYc5oj8nISHaIIilBD5pEJF+ZI4/GueshzGVdIaMY9o0XCPt1xX79eYHe&#10;hU2koFDiFpF8Z5w0nNNaR9PHzmgHK/4ifHww4aP9sb//muzwRAq0PXaVe55XY4dDFljv+/7yxIQk&#10;IkWFKZWJueha7GmtCceNhu++IrynG6b5uZi2nTClMpMdokiBE0+LezqwEPgW+Br4BVjqed4Sz/Ma&#10;JTA2ESkizEGH4NzcH6frXVCxMvaD/0a7j02bhA23Jjs8kQIlnsT9AXCV7/vlfd+vCHhEW3u2AR5J&#10;YGwiUoQYYzDHN8S553FMx8shaxP2xccJB/fE/vBdssMTKTDiSdzH+b7/QvYL3/dfB07wff8roFjC&#10;IhORIslkZOCcfQHOoJGYU5rD4p8J7+9FOOpB7Iq/kx2eSNLFk7jTPc+rl/0i9nWa53klAM3fEJGE&#10;MOUr4VzTA6fX/XDokdH8775dCCe+gs3alOzwRJImnnncvYCpnufNI0r0RwIXA/cA4xMYm4gI5vCj&#10;cO58APvZZOwbL2DffAn7yfs43tVQ/1SMMckOUSRf7bHF7fv+20BtoufZQ4A6vu9PBgb5vt83wfGJ&#10;iGAcB6fxGTiDnsS07gCrVhCOHEL4cF/skkXJDk8kX+0xcXue5wDXAjcDdwI3eZ6X7vv+mkQHJyKS&#10;kylZCueCq3D6j4BjToT53xIO6E748lPYdfqRJEVDPF3l9wHHAY8SJfrrgQeAHvEU4HleQ2CI7/vN&#10;Pc87Gngq9tYPwLWx/b1FROJmqh5MWre7sXNmEb7yDHbKW9gvpmHaX4I5rXWywxNJqHgGp50FtPV9&#10;//98338DaA+cHc/NPc+7DRgFFI8dGgz08n2/KWCAtnsfsohIxBxzIk7/4ZgLroItW7AvPUk4sAcb&#10;58xOdmgiCRNP4nZ839+c/cL3/U3A5t2cn9OPQIccrzv6vj/d87xiQFXgn7gjFRHJhUnPwGndIXr+&#10;3bgl/PYLf/X6N+GTQ7HL/0x2eCL7XTxd5V97nvcI8FjsdVeiVdT2yPf98Z7n1czx2saWUP0AWAV8&#10;s5fxiojkypSrgLmyO/b0c0h/43myZk/HfvsF5qyOmNbnY4oX3/NNRFJAPIm7KzAc+JSoe3sScFNe&#10;C/R9fzFQ2/O8a4hGql+5p2uqVauW1+KSKlXjjpfql9oKbf2qVcOe2pT1U99l1XPDCSeMw5kxhfLX&#10;3EzJJmcUmuljhfb7F6P67doeE7fv+6vZIbl6nlcX2Os9uj3PexPo6fv+j8AaIK5FiJcuXbq3RSVd&#10;tWrVUjLueKl+qa0o1O+fo46Hex7HvP0qW9//P5YPuRNqj8HpdD3mkFrJDnGfFIXvX1Gv3+4Sezwt&#10;7tx8BpTNw3VDgOc9z9sErCeaZiYikhCmRElMx8uxTVoR+s/ANzMJB/bAnHYmpv2lmDJ5+TEmklx5&#10;Tdxx9zX5vr8IaBT7+jOgSR7LFBHJE1PlINJu7IOd9xXhK6OxH72L/eJjTLtLMM3OxqSlJTtEkbjF&#10;M6o8N3a/RiEikg9M3fo4dw/DXHQNWLDjniYc0B37vcbJSurIa+IWEUlJJj0d54z2OIOfxDQ9E37/&#10;lfDhvmx94l7sX8uSHZ7IHu2yq9zzvDXk3rI2QKmERSQikg9MmXKYy2/Enn424bhR8NUMwjmzMWd2&#10;wJx9PqZEyWSHKJKr3T3jrreb90RECgVT83Cc2+/DfvEx9rXnsW/72E8/xJx/Babh6YVm+pgUHrtM&#10;3LFBZSIihZ4xBnPyadjjTsa++zr23TewzzyM/eidaPpYzcOTHaLINnrGLSISY4qXwGl/Cc7AJ6BB&#10;I/jxe8LBtxC+8Bh29apkhycCKHGLiOzEHHAgaV164dwyEKrVwH78HmGfLoTvv4ndsiXZ4UkRp8Qt&#10;IrILps5xOH0fxfzrejAG6z9DeE837Nwvkx2aFGFK3CIiu2HS0nBatImmjzU7G/5YSjisP1sfG4T9&#10;s/AuyykFV15XThMRKVJMZlnMJV2wp59FOG50tHzq3C8xZ7TDtPEwJTRLVvKHWtwiInvBVK+F03MQ&#10;Tuc7oFwF7KQ3ouffn36IDcNkhydFgBK3iMheMsZgTmiMM/AJTLuLYcM67HPDCIfcjl24INnhSSGn&#10;xC0ikkemWHGctp1wBozEnNQUFi4gvPdWwueGYf9ZmezwpJBS4hYR2UemUmWc62/DufVeqF4L++mH&#10;hH06E056A7tlc7LDk0JGiVtEZD8xbj2cvg9jLukC6enY154n7HcT9tsvkh2aFCJK3CIi+5Fx0nCa&#10;nY0z6ClMy7bw9zLCEQPZOuwe7LLfkh2eFAKaDiYikgCmdCam03XYpq0JXxkFc2cTfv81pkUbTJtO&#10;mFKlkx2ipCi1uEVEEsgcXAOnxwCcG3pDhQOw778ZPf/++D1NH5M8UeIWEUkwYwym/ik4Ax7HnHcp&#10;bNqIfeExwntvxf74fbLDkxSjxC0ikk9MRjGccz2cQU9iGp4Oi34kHHoH4TMPY1ctT3Z4kiKUuEVE&#10;8pmpUAnn2p44dwyBGodjZ0yNVl97+1Xs5qxkhycFnBK3iEiSmCOOxrnrQczlN0Kx4tjxLxL2uxH7&#10;1QystckOTwooJW4RkSQyThpO0zOj7vNW7WHFX4RP3Ev4aD/s0sXJDk8KICVuEZECwJQqjeNdg9Nv&#10;BNRrAN99TXhPN8Jxo7Dr1iY7PClAlLhFRAoQc1B1nG79cG7sCwcciP1wQjR97KN3seHWZIcnBYAS&#10;t4hIAWOMwRx3Ek7/xzDnXwGbN2PHPEE46BbsgnnJDk+STIlbRKSAMhkZOGedjzNoJObUFvDrQsIH&#10;7mT50N7YFX8lOzxJEiVuEZECzpSviHP1zTh3PgC1arN+2nuEfbsQThyHzdqU7PAknylxi4ikCHOY&#10;i9Prfir26A8lS2PffJnw7q7Y2dM1fawIUeIWEUkhxnEofUYbnIEjMa07wqoVhE8OJXyoD/a3X5Id&#10;nuQDJW4RkRRkSpbCueBKnHseg2NPgmAO4YCbCV96Ert2dbLDkwRS4hYRSWHmwGqk3dQXp3s/OPAg&#10;7NS3o+VTp7yN3arpY4WREreISCFg6p2A02845sKrIdyKfflJwoE3Y4M5yQ5N9jMlbhGRQsKkZ+Cc&#10;eV40faxJK1i6mPDBu9j65BDs8j+THZ7sJ+mJLsDzvIbAEN/3m3uedzwwHNgCbAIu931fkxFFRPYj&#10;U7YC5oqbsKefRThuFMz+lPDbWZjWHTBnXYApXjzZIco+SGiL2/O824BRQPa/kkeBrr7vtwDGA70S&#10;Wb6ISFFmDj0S546hmGtugdKZ2ImvRPO/Z07T9LEUluiu8h+BDjleX+T7fvYDl3RgQ4LLFxEp0owx&#10;OKc0i6aPnXMhrFmFHfUg4QN3Yhf/lOzwJA8Smrh93x9P1C2e/foPAM/zGgFdgUcSWb6IiERMiZI4&#10;HS7DGfAE/H97dx4mRXX1cfx7a0CQTcUFHRVJNLhAjEsUAwoCGhElhKgXxO1NIojii0ZFZVEWIahR&#10;UJYgrqiJxqNvMGo0GgWNEkUhQFiiuEIEQaKCCMpW9f5RPWYYB5ylu2uq5/d5Hh6qq7tunfP0zJy+&#10;t7ruPeI4eHsx4agrCB+cRLRubdLhSSW4XA+XeO8PAB42s7aZxz2BQUB3M1tagSY0niMikmVfzZ3F&#10;Z3feypZl7+EaNmaXcy+iUdczcXVy/tUnqThX3s68vkPe+3OBvsCJZramosetWLEid0HlSHFxcSrj&#10;rijll27KL92ykl+z/YkG3YJ76RmiJx5izZRbWPPEIwS9+uAOOyI7gVaR3r/4NduTt9vBvPcBcDvQ&#10;CJjmvZ/uvR+Wr/OLiMi2XJ06BJ27EYy6A9e+C6z8kHDc9WydNJpo9cqkw5PtyHmPOzMc3jbzcPdc&#10;n09ERCrHNd4Fd94lmdvH7oR5swgXzsGd/FNc17Nw9XdOOkQpRROwiIgIAK75dwkGjsH1HQhNdiV6&#10;5rH49rHXZuj2sRpEhVtERL7mnCM45gSCkZNxp/eC9V8Q3TOO8KZriD54O+nwBBVuEREph6tXj6B7&#10;bwkZ2cEAABG6SURBVIKRk+DotvDum4S/vopw6niizz9LOrxaTYVbRES2y+3RjKJ+1xJcOQqKmxPN&#10;fD5efey5aURbNicdXq2kwi0iIt/KHXI4wXW34Xr3g6CI6NH7CEcMIFowJ+nQah0VbhERqRBXVETQ&#10;sWu8+ljHrrDqI8LxI9g6fiTRqsK977qm0RQ5IiJSKa5RE1zvfkTtM6uPLZhNuHge7qRuuNN64nZu&#10;kHSIBU09bhERqRK3XwuCK0cR9LsWdm1K9Oy0+PaxmS8QhWHS4RUsFW4REaky5xzu6LYEIyfhuveG&#10;L9cTTb2d8Marid57K+nwCpIKt4iIVJvbqR7B6b3i5UOPOQHeX0I4ZiDhveOI1nyadHgFRYVbRESy&#10;xjXdk6DvQIKBY2D/7xC9OiO+feyZ/yParNvHskGFW0REss61bEUwdCzuvEugbl2iP95POPxSovmv&#10;V2r6VOdcuY/L7q9N9K1yERHJCRcU4dp3ITr6eKInHyaa8WfCiaOg1ZEEPfvg9tmv3OM2bNjIokWf&#10;M336chYu/JTWrZvSpk0zVq3awJYtEUuWrOGddz7n8MOb0qnTvrRs2Zi6dWtPIVfhFhGRnHING+F6&#10;9SFqfwrhI3fDormEI/4X1/F0XLdeuAYNv37t5s0R99//T/r3f4mSjvlTTy2ldeum9O79PYYMmfX1&#10;/qefXspNN81l/Pjj6dZt/1pTvDVULiIieeGKmxNcPoKg/2BouifR838iHNqP8OXniMKtACxZsm6b&#10;ol3irLMO3KZol4giGDDgFZYsWZenLJKnwi0iInnjnMMdcRzBiIm4HufBpo1ED0wkHH0V0TuLmT59&#10;+TeKc3FxA5Yt++Ib+0tEEcyYsTz3wdcQGioXEZG8c3V3wnU9i+hHnYj+eD/Ray8S3nQtP+Qw9q5/&#10;ECu/+u/sa3vvHRfuHVm48DOcc7Vi3XD1uEVEJDFut90JfnkFwbU3wwEHcSyLebH9n7n0wEXUC+Lh&#10;85UrN9C8eaMdttO69W61omiDCreIiNQA7sBDCAbfwkcn92H91jpcffACXmj/NKc0+5AVK9bTvHkj&#10;tncHmHPQseO++Q04QSrcIiJSI7ggoFmP05nzkzHc+d7B7FN/A3cd/QoPHfsisx5/g9Gj23yjeDsH&#10;EyacQMuWjZMJOgG6xi0iIjVG3bqOcy5sw8xD9+KxZ+Zx+Ft/5Pg93qOdM5YuX8kdY09j8Qebeffd&#10;tbRurfu4RUREEtegQT1atWpCq1btca4D4fzXCR+5hxbvv0iL1XPo2v1cgoGngKudg8a1M2sREUmF&#10;KIpwhx9DMGIC7sz/gS1biH4/ma0jf0W0ZGHS4SVChVtERGo8V6cuwSk/Ixh1B65tZ/jwfcLfDCac&#10;cjPRJ6uTDi+vVLhFRCQ13C67Efz8MoLBt8B3WhLNfoXw+osJn3iYaNPGpMPLCxVuERFJHfedlgTX&#10;3oz7+eWwc0OiJx8mvO4SotmvFPz93CrcIiKSSi4ICNp2Ihg1GdflDPj8M8IpNxPeOpTow/eTDi9n&#10;VLhFRCTVXP0GBGdcQDBiIvzgWHhrAeHIXxH+fjLRF58nHV7WqXCLiEhBcHsVU3TpUILLhkOzYqIX&#10;nyEc0o9w+lNEW7cmHV7WqHCLiEhBca2PIhg2Hud/CVFI9PCdhDdcTvSv+UmHlhUq3CIiUnBcnToE&#10;J3ePbx874cewYhnh2OvYOnkM0eqVSYdXLSrcIiJSsFyTXQnOv5RgyK1w0KHwj1cJr+9P+PjviDZ+&#10;lXR4VaLCLSIiBc8dcBDB1TfiLrwSGjUh+rMRXncJ4ayXUnf7mAq3iIjUCs45gjYdCG74La6rh3Vr&#10;ie6+lfDmQUTL3k06vArLeeH23rfx3s8os2+s975vrs8tIiJSlqu/M0GPcwlGToIjj4N3FhOOuoLw&#10;gYlE69YmHd63yunqYN77gcB5wBeZx3sADwDfA97M5blFRER2xO25N0WXDCb613zCP9xF9PJzRLNn&#10;4n7SC3fiabg6NXMBzVz3uN8BepR63AgYBjyY4/OKiIhUiDv0BwTX347r1RccRI/cQzjyMqJFc5MO&#10;rVw5LdxmNg3YUurxB2b2BlB7VjwXEZEazxUVEXQ+nWDUFFyHLrByOeFtw9g6cRTRxx8lHd42auY4&#10;QBnFxcVJh1AlaY27opRfuim/dFN+OTszXD2KTWeez5opt7Bx/uuEi+bSuMc5NOn5C4KdG2TnLNXI&#10;L1+Fu1o97BUrVmQrjrwpLi5OZdwVpfzSTfmlm/LLg/qNiAYMw82eSfTYvax7dCrrnnsCd8YFuDYd&#10;cEHVB6wrkt+OCnu+bgcre5Ncum6aExGRWsc5R3DM8QQjJ+O69YINXxDdO47wpmuI3n87sbhy3uM2&#10;s6VA2zL7Rub6vCIiItng6tXD/aQ3UbuTiB69j2jOTMJfX4lr1xnX43zcLrvlNR5NwCIiIlIBbve9&#10;CPpdQ3DVaNivBdHMFwiH9iN8dhrRls15i0OFW0REpBLcwd8nGDoOd04/KKpD9Nh9hMMHEC2YnZfz&#10;q3CLiIhUkisqIjixK8HoO3AdT4PVHxGOH8nW8SOJVi7P6blTcTuYiIhITeQaNsb1voioQxfCP9wF&#10;C2YTLp6H69wNd3pPXJZuHytNPW4REZFqcvseQHDFDQQXD4JdmxI9Ny2+/j3zeaIwzOq5VLhFRESy&#10;wDmHO+pHBCMn4bqfA199STR1POGYgUTvZm95DhVuERGRLHI71SM4vSfBDZNxx7aHD94mvPFqwnvG&#10;Ea35pNrtq3CLiIjkgGu6B0GfqwiuvhGaf5fotRmEQy/mc5tKtLnqt4+pcIuIiOSQ+95hBENuxZ3X&#10;H+ruxNr7JxIO6080bxZRVPmJRFW4RUREcswFRQTtTyEYfQeNup8Nn64mnDSa8LbhRB/9u1JtqXCL&#10;iIjkiWvQiN36XkkwbDwcdiQsnks4YgDhI3cTbfiiQm2ocIuIiOSZ22d/gsuHE/QfAk33JHr+CcKh&#10;FxP+7VmicOsOj1XhFhERSYBzDndEG4IRk3A/Ox82bSR6cBLh6Ct3eJwKt4iISIJc3boEp55JMGoy&#10;7riOsOy9Hb5eU56KiIjUAG7X3XG//BVRt547fJ163CIiIjWI26t4h8+rcIuIiKSICreIiEiKqHCL&#10;iIikiAq3iIhIiqhwi4iIpIgKt4iISIqocIuIiKSICreIiEiKqHCLiIikiAq3iIhIiqhwi4iIpIgK&#10;t4iISIqocIuIiKSICreIiEiKqHCLiIikiAq3iIhIiqhwi4iIpIgKt4iISIrUyfUJvPdtgBvNrKP3&#10;/kBgKhACC82sf67PLyIiUkhy2uP23g8E7gLqZXaNBQabWQcg8N53z+X5RURECk2uh8rfAXqUeny0&#10;mb2c2X4GOCnH5xcRESkoOS3cZjYN2FJqlyu1vQ7YJZfnFxERKTQ5v8ZdRlhquzGwpiIHFRcX5yaa&#10;HEtr3BWl/NJN+aWb8ku36uSX78L9D+99ezP7G3AqML0Cx7hvf4mIiEjtkO/CfRVwl/e+LvAv4LE8&#10;n19ERCTVXBRFSccgIiIiFaQJWERERFJEhVtERCRFVLhFRERSJN9fTitoZaZ3PQJ4CliSeXqymT2a&#10;XHTVVya/PYlnxdsVKALON7P3Ew2wmsrk9zDQjPiuhhbAq2bWO8n4qqucn8/JwGZgiZldmGx01Vcm&#10;v6OI8/sKmGdmlyUbXdV57+sA9xL/HO4EjAYWUyDTR5eXn5k9mXluLPCmmd2ZXITVs533bxkwgXie&#10;k43Efz9XV7RN9bizpJzpXY8GbjWzTpl/aS/aZfO7GfidmZ0IXAccklBoWVE2PzM728w6Ec/89xlw&#10;eYLhVVs579/1wHAzaw/U996fllhwWVBOflOAAZnpldd679P8oetc4D+Z96oLMJHCmj66dH6nAhO9&#10;97t7758GuiUbWlaU9/7dBvTP/I2ZBlxbmQZVuLPnG9O7Aqd571/y3t/tvW+YUFzZUja/dsB+3vu/&#10;Ar2BF5MIKovK5ldiBDDBzD7OczzZVja/ucAe3ntHPBnS5kSiyp6y+e1nZrMy238Hjs9/SFljxB+O&#10;IR7d2gIcVUDTR5fOLyD+WWwEDAMeTCqoLCr7/m0GeprZgsy+OsCXlWlQhTtLypnedRYwMPOJ+D1g&#10;eBJxZUs5+bUAPjWzk4F/U8lPjDVNOfmRuRzQiXhIMtXKye9tYDywCNiLlH/wKie/d733J2S2uwGp&#10;/eBsZhvMbL33vjHwKDCEApo+urz8zGypmb1BAUzAtZ38Pgbw3rcF+gPjKtOmCnfuPG5mczPb04Aj&#10;kgwmBz4BnsxsP0k8wlBozgQeMrNCnOzgdqCdmR1G3KsZm3A82fYLYHBmRGgV8J+E46kW7/3+xDNN&#10;3m9mf6CK00fXVGXyeyTpeLKtvPy89z2B3wJdzeyTyrSnwp07z3rvf5jZ7gzMSTKYHHgZ6JrZbk/c&#10;cysEpT/hn0Q8DFmIPiHuqQGsIP6SYSE5DeidGRHaA/hrwvFUmfe+GfAscLWZ3Z/ZPdd73z6zfSrx&#10;72MqbSe/glFeft77c4l72iea2dLKtqlvlefOxcAE7/0mYCXQN+F4su0q4G7v/cXAWuLr3IWgdO+6&#10;JfFljkLUB3jEe78Z2JR5XEjeBqZ779cDM8zsL0kHVA2DiD9YXee9v574Z/Qy4r8vhTB9dHn5nWpm&#10;G9n29zGtyuZXBLQClgLTvPcR8JKZjahog5ryVEREJEU0VC4iIpIiKtwiIiIposItIiKSIircIiIi&#10;KaLCLSIikiIq3CIiIimi+7hF8sx7HxAvWnI28T2dOxGvJHe9mW2qQnv3AQvMrEKzn3nvOwO3EN8j&#10;u08mhg8zT48hnlinwu1VMtYOwEQz+34ljwuBPczs0zL7rwRam9nPsximSI2mwi2Sf3cQzy3dyczW&#10;ee93Bh4iXt3qglyf3MxeAI4E8N4PA3Y3swElz3vvu27v2CypyuQROzpGk1FIraLCLZJH3vsWxD3t&#10;vc1sPYCZfem9vwhomyniy4FjzeydzDHPEa/dOz3zfzviFYYeN7OhZdo/lHjJwKbEPenxZja1CqG2&#10;896fQbwm+ULg7EycXwF/Ag4HzgE2EM97vs35Mqvh3QccRDyv9hwzuyjTduPMeueHEC/D2cfMZnrv&#10;mwCTiOf1D4G/AIPMLCQzFW1mbeMJxNPRrgI+JuXzdItUlq5xi+TXUcCikqJdwsw+NrPHzexL4tXI&#10;+gB47w8knnr1KeAGoJ6ZHUzcY25Xar5qvPdFxKsPXWNmxwAnAgO998dWIc5i4pXRWgL7AT/L7N8J&#10;+JOZHQrMJ55qs7zz9QAamdlRwLGZ+L6baWNf4rXqjwTu5L8r500gXrf4+8APgR8QT61bWn/iDwOH&#10;AD8GmlchN5FUU+EWya+Qb/+9mwyclynEfYC7MiuUdQbuATCzzWbW0cz+Vuq4lsCBwL3e+7nAS0B9&#10;MsPilfS4mW3M9HYXEi/9WeKVCpzvFaCV934G8ZKvt5lZybzv75rZ7Mz2vFJtdwEmluRHfEnh1Mxz&#10;JcPhnYlXbNtqZhuA31chN5FU01C5SH69DhzqvW9Yutftvd8XmAKcYWZve+//CfyUeDi6ZJW5LZS6&#10;nuu93494qLpEEfBZppdb8pq9qNpQ8uZS2xHbrpr2xbedz8w2ee8PIu6FdwJe8N5fSrwq2fbaLvuB&#10;JgDqltlXNpYtiNQy6nGL5JGZrSDuJd7rvW8MUOra7urMikgQr9P7G+A1M1uV2fc8cIH33nnv6xEP&#10;U7cv1fxbwFfe+3My7e5P3FvO1Vrp2z2f974fMNXM/mpmg4iXNWydOc6V21r8mv6ZtuoRr6j3XJlj&#10;/gKc772v572vD/TMck4iNZ4Kt0j+XUK8FOPfvff/AF4lLnill9Z8CmhEPGxeYgRxb3U+8fruT5nZ&#10;4yVPZoaXuwMXeu/nExe5IWb2aiXjK/st7ai87W853wNA4L1f7L1/A2hM/CW28tovMQBo5r1fkMnx&#10;TeDXZY6ZQpz7QmAGhbvsqsh2aVlPkRrIe98WmFLZ+51FpPDpGrdIDeO9nwp0AM5LOBQRqYHU4xYR&#10;EUkRXeMWERFJERVuERGRFFHhFhERSREVbhERkRRR4RYREUkRFW4REZEU+X8qM2PTl1V7nwAAAABJ&#10;RU5ErkJggg==&#10;">
+
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAe4AAAGMCAYAAAAcK0EHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz&#10;AAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmcTuX/x/HXdWbGOvZIEmlxEi20KEtZkhZLVCff9v1L&#10;iqRFIrIU7ahUtHxL0Wnx60uLFqSURBvK0SKKtFiyG5zr98e5x3cwuA333HPPvJ+Ph4e5z33OuT7X&#10;Pcxnrutci7HWIiIiIqnBSXYAIiIiEj8lbhERkRSixC0iIpJClLhFRERSiBK3iIhIClHiFhERSSFK&#10;3CIiIikkPdkBiOQn13VPA6YCTwZBcEOO41cADwZBUDkBZZ4OTAEygyBYH8f5xwCVgiCYug9llgXu&#10;AC4ADgGWAROBe4MgWJbX++YhjgOAVkEQjI29ngJ8EQTB7a7rGuA54ELgT6A/8EAQBFX2Q7nbfYau&#10;64ZAmyAI3t7Xe++h3DuBBkEQXJjIcqRoU4tbippLgAVAJ9d1i+/wXiJXI9qbe78JHJ3XgmLJ8nPg&#10;dOAGwAWuiv09y3Xdw/N67zy4H+iQ43UH4J7Y16cCl8eONQbGsQ/13sGOn2FV4P39dO9cua57GTCQ&#10;xP47ElGLW4oO13WLEbVAbwaeAs4HXk5qULkz+3j9o8Aq4PQgCLbGjv3quu404F3gGaDZPpYRr+3q&#10;EgTBqhwvKwA2CIL3chzblKBy/9xP992J67olgCcAj+iXQpGEUuKWoqQNUBZ4i6jr+mp2SNyxrs6e&#10;sZcvALcGQRC6rptGlBAvAMoBs4FbgiD4Inbd4cCDRK3cEHgj9v7aHe5fE1gI1AuC4LvYsW3d9LGu&#10;5JrACNd1LwiCoIXrugcCI4CzgLWx+HsGQbB6xwq6rluBqOu5Q46kDUAQBNZ13X7Ap67r1gmC4HvX&#10;dRcSdU8/kVt8rutWAR4BWsXq/SswOAiC52LnTwE+Ao4HzgT+BvoHQfBsrKwrYudtDYIgLburHJhH&#10;1E2O67pbiVrhi8jxuMJ13WOBh4BTgBXAyCAIhsTeOwm4D2hI9HPsG6BbEAQzd/EZbusqd103A+gd&#10;i+0gYFbs85y5mzrdEwTBMzt+3jFVYuWdBNwOlN7FeSL7hbrKpSi5BJgeBMEKosTaLJaosh1A9IO6&#10;Wezci4l+EAPcBLQF2hF1wS4AXgVwXbc88AlRa7ExUddvE6KWbW5y60rNPtYR+I0osXSMHRsPbCVK&#10;Um2Aw4i6lXNzAlEi+yy3N4MgmAFsBBrt4vod43uR6HNpDtQh6oIe6bpuzrEAtwNvE30u44EnYu8/&#10;CPjABKKu6pzGAZfFyqoaO3db2a7rVgI+JPosTgSuB3q5rnul67qZsfK+BI4h+lzWEvWiQO6fYU6P&#10;Ef3S1oUoOc8D3o/9grSrOj2+Q523CYJgcRAELYMg+D6390X2NyVuKRJc1y0HnAO8Hjv0f0Qt4ytz&#10;nLYFuDgIgrlBEEwCBhE9IwY4lCjh/RoEwS/ALcAVsQFWlxL9X7o8CILvgyD4OHbfC3fxPHmXXeFB&#10;EKwkStJrgiBY5bpuc6AecFns3l8SJbyzXNetk8stDoj9vWZXZRC1Xg/Yzfs545sA/DsIgnlBEPwM&#10;3AsUA2rnOGdKEARPxz6XPrH3jwuCYB2wAdgUBMFfO9RzE1F3PkEQ/JXLoL1OQBZwXRCZRJRo1wKl&#10;gKFAryAIfgmC4FtgJNHntNNnmPOmsX8HVwM3B0EwKQiCIHbfX4Eb91Sn3XxmIvlGiVuKiouIfviO&#10;BwiCYDlRd+gVOc5ZEgTB7zlezwYOjo3QHglkEj0r/hj4N/BdEASWqCX6dRAEWTmu/YIo8dTdx7iP&#10;Jup6Xem67hrXddcAAdEvHUflcv7y2N/Vd3PPcsSSZhxGAqe4rjvcdd13ge+IWsVpOc75IfuLIAiy&#10;f2HIiPP+u1IH+DYIgi057j02CILXYs+rRwNdXdcdHXt2/x/i+3lWO3bejBz3tcCnbP+9SkSdRPYL&#10;PeOWouKS2N8LXdfNPmYA47puy9jrrTtck50INgdBELiuWwtoDZwNdANudF23IVFLPDeG7RMc5N5N&#10;vrv/h+nAL8AZ7NxS/yOX82cR9RycHLtuO67rnkD0i8AXu4gnPce5BpgEVCPq2p5M1K0c7HBNFjvb&#10;1wF2Wbu6h+u6BwEzgfnAO7HYKgNj4rjvxl3c12H771Ui6iSyX6jFLYWe67o1iJ459yPq7sz+cwJR&#10;1+vVsVOrx55XZ2sELAqCYIPrupcCFwVBMDEIgq5EU6uqxO77PXD8DtPLTiZKgjs+98xOCGVyHNux&#10;Oz1nMv2eKHGuDYLg51h39VaigXI7zXeOdRP7QL/YICxc123suu63ruu2IZquNDvW5Z4dz46xZJdf&#10;H2gBnB0EwYAgCP6PaCQ4xJ/E8jo1agFQLzYokFg97nZd9xXgX0S/TLUKguDhIAg+IJqrHk+5PwKb&#10;2fkZ/6lEvQkiBZ5a3FIUXEr0rHX4jiOxXdf9D3AtUQs0HRjruu4dRAnsTqJFTCAajT7Add3lRD/g&#10;2xAlry+BpcDdwAuu6w4AKhFND3o/CIL5sUFP2YnuD6LnqT1d1+1F9AvElTvEuxaoExsM9X6svFdc&#10;172VqIv8MaJu+192Ud+biR4DTHFd9x7gJ2A68F+ihJYzaX0BXB7rBi/B9vOQlxF77u+67ktEv6wM&#10;i72/4xz4XVkL1HVdt2YQBIvivAbgJaIFWZ5wXfch4IhYvboT/bJxoOu65wJziQbO3QXRlL/YI4tt&#10;n2HO5+uxX8JGAA+7rruOaAR9d6JR4aP2Ij6RpFGLW4qCi4FxuU2fIkqCxYhGhH9HlMimET3bfTAI&#10;glEAselSj8WOzyca5XxBEAQ/BUGwgWg0ejmiLtxXiVZnOz9HOTZ2H0uUqOsQdTt3J/oFIadhRL9s&#10;vBs7vx3Rs+vJsT9LgXNi7+0k9vz+1FgMjxEltzZE09veAMbFWt8QJbwlRKPQnyfqlQhj91kaq+d1&#10;RC3/R4HHgW+Jeit2JWdczxNNuZoXm1oWl9hz5bOJnuN/HSv3niAIXiTqURhFNJ3sm1h818bKzY5r&#10;22eYS0x3Aq/Erp9N9L1oFuvN2PHc3OokklTG2sT+e/Q8ryEwxPf95p7nHU/0g28zsMD3/WsTWriI&#10;7MR13TOJupqnJDsWEdl7CW1xe553G9FvxtndancD/X3fPw0o4XneuYksX0R2FgTBe0raIqkr0V3l&#10;P7L9OsVfAQd4nmeIBsRsTnD5IiIihUpCE7fv++OJBrdk+wEYTvRsrwrRMzgRERGJU36PKh8GNPZ9&#10;f77neTcAD7P9akW50aAQEREpinKddpnfiXs5/1uKcSm7Xy95m6VLlyYsoESpVq1aSsYdL9Uvtal+&#10;qU31S23x1K9atWq7fC+/E/d1wCue520mtg5xPpcvIiKS0hKeuH3fX0SsZe37/nSilaZEREQkD7QA&#10;i4iISApR4hYREUkhStwiIiIpRIlbREQkhShxi4iIpBBt6ykiIinh66+/ZsCAARx66KEArFu3jmrV&#10;qtGnTx/S0rZt3Y61lpEjR7Jw4UKysrIoWbIk3bt356CDDtpjGVlZWQwePJhVq1ZRqlQpevXqRbly&#10;5bY7Z+zYsUyePJnSpUtz0UUXceqppzJ27FhmzpyJMYY1a9awcuVKXnvttW3XjBkzhoULF9K3b999&#10;/hyUuEVEJGXUr19/u+Q3aNAgpk+fzmmnnbbt2MyZM1m+fDkPPPAAANOnT+eJJ55g4MCBe7z/m2++&#10;yWGHHcYVV1zB5MmTefHFF7nxxv8t8Llw4UImT57MyJEjCcOQG2+8kRNOOIF//etf/Otf/wKgd+/e&#10;dO7ceds1n3/+OZ9//jlVqsS9s+1uKXGLiEhK2rx5MytWrKBMmTLbHS9fvjwLFixgypQpNGjQgMaN&#10;G3PKKacA8NFHHzFmzBjKly9P6dKlOfXUU2nduvW2a+fMmbMtATds2JAXX3xxu3svWrSI448/nvT0&#10;KH1Wr16dn376iTp16gAwbdo0ypQpwwknRFvDL1myhLfeeourrrqKt956a7/UW4lbRET2Wvjqc9jZ&#10;0/frPc0JjXEuvGq353z11VfccsstrFixAsdxaNu2LfXr19/uHNd16dmzJxMmTGDEiBFUqVKFG264&#10;gbp16zJy5EhGjx5N6dKl6dWr1073X79+PaVLlwagVKlSrF+/frv3DzvsMF5++WU2bNhAVlYW8+bN&#10;o23bttveHzt27LYegQ0bNjBs2DB69+7NL7/8kpePJFdK3CIikjKyu8pXr17NbbfdRtWqVXc65+ef&#10;f+aQQw7ZlkBnzZpF//79eeaZZyhbtiyZmZkAHHfccTtdW6pUKTZs2ABESTz73Gw1atTgvPPO4447&#10;7qBKlSrUqVNn2zPwRYsWkZmZuW2d8VmzZrFy5UoGDBjAmjVrWL58OWPHjqVnz5779BkocYuIyF5z&#10;LrwK9tA6TqSyZcvSu3dvevTowejRo6lYseK292bPns2iRYvo2bMnxhhq1qxJyZIlqVChAhs3bmTV&#10;qlWUL1+eIAho1Gj7va7q1avHjBkzcF2Xzz//nGOOOWa79//55x/Wr1/P8OHDWbduHbfffju1atXa&#10;Vm7Dhg23ndu0aVOaNm0KRAPrJkyYsK0bfl8ocYuISEqqWbMm559/PiNGjKBfv37bjnfs2JEnn3yS&#10;a6+9lszMTIwx3HXXXQD06NGD3r17U7p0aTZt2rTTPdu3b899991Ht27dyMjIoE+fPgC8+uqrVK9e&#10;nVNPPZXFixfTpUsXMjIy6Ny5M8ZEu2/+9ttv255tJ5KxtsBvd21TcXs3bUuX2lS/1Kb6pbb8qt+o&#10;UaOoUaPGdoPT8sNebOuZ637cWoBFREQkhairXEREiqTrrrsu2SHkiVrcIiIiKUSJW0REJIUocYuI&#10;iKQQJW4REUkIa2H9+q1s2VLgZy+lFCVuERHZr7Zutcybt5rBg7+hXbv3uPjiKUyatJS//87a72WN&#10;Hz9+n+/RtWtX/vjjj72+bvHixfTo0WOfy99bGlUuIiL71bRpf3LFFZPZuvV/Le3p05fRqlV17r+/&#10;IVWqFN9vZY0ZM4YOHTrst/vtrezFV/KTEreIiOw3v/22gc6dp22XtLO9//5vfPppLc4775A83vs3&#10;hg4dSnp6OmEY0qBBA9asWcOwYcO47rrreOCBB1i3bh3Lly+nffv2tGvXjh49enDEEUewcOFC1q9f&#10;T//+/alSpQqjR49m1qxZVK5cmdWrVwPw119/8eijj5KVlcWKFSu4+uqrady4MVdffTXVq1cnIyOD&#10;rl27MmjQIAAqVKiwLbbRo0fz9ddfE4Yhp512Gp06dcpTHeOhxC0iIvvNggX/sHbt5l2+P2LEHM44&#10;oxqZmWl7fe9Zs2ZRp04d/v3vfzNnzhzKlSvHhAkT6N69Oz/88AMtW7akSZMmLF++nB49etCuXTsA&#10;6tSpQ9euXXnmmWf48MMPadCgAXPmzOHJJ59k/fr1XHbZZUDU9e15Hscddxzz5s3j+eefp3HjxmzY&#10;sIErrriCww8/nOHDh9OyZUvOPfdcpkyZwoQJEwCYPHkyjzzyCBUrVmTSpEl5+OTip8QtIiL7zZo1&#10;u07aAH/8sYGNG7fmKXGfc845jB07lttvv53MzEyuueaabe9VqFCB1157jWnTplGqVCm2bNmy7b0j&#10;jjgCgMqVK7Ny5Up+++03XNcFot3AsjcJqVSpEi+++CJvv/02AFu3bt12j0MOiXoJfv31V9q0aQNE&#10;G5JkJ+7evXvz9NNPs3LlSk4++eS9rtve0OA0ERHZb6pUKbnb9489thKZmXlrM06fPp1jjz2Whx56&#10;iNNPP52xY8eSvd+G7/vUrVuX3r1706xZM3Luw7Hjc+iaNWsyf/58INoze9GiRQA8++yztG7dmjvv&#10;vJP69evneo9DDz2UuXPnAmy7x5YtW/joo4/o27cvDz/8MO+++y5//vlnnuoYD7W4RURkv6lduyw1&#10;a2ayaNHaXN+/4Ya6lCiRtzaj67oMGTKEF198EWvtttHg9957L+eccw7Dhw9nypQplC5dmvT0dDZv&#10;3pzr4LEjjjiCk08+mc6dO1OpUqVtz6qbNWvGyJEjefnllznggAO2PfvOeY9LL72UwYMHM3Xq1G17&#10;gaenp1OmTBluuOEGSpQowUknnUSVKlXyVMd4aHewBNHuPalN9Uttql9yBcEaLrnkQ37/ff22Y8ZA&#10;v34ncsklh1Oq1O67yQt6/fbVvu4Opha3iIjsV65bhokTz+b771cxf/5KKlQowfHHV+Kww0pTrJie&#10;0O4rJW4REdnvqlYtTtWqB9K8+YHJDqXQ0a8+IiIiKUSJW0REJIUocYuIiKQQJW4REUkIYy3p69fj&#10;5FgMRfadEreIiOxXZutWSs2bR/nBg6nUrh2VLr6YzEmTKPb33/t036ysLN566629uubbb79l4cKF&#10;+1RuQZPwUeWe5zUEhvi+39zzvLHAgURz0w4FPvN9/+JExyAiIvmn9LRplLniCkxsydA0IGP6dLJa&#10;tWL1/feTlcfFSVasWMHbb7/NueeeG/c177zzDs2bN9+2rGlhkNDE7XnebcBlwFoA3/f/FTteHpgM&#10;3JzI8kVEJH8V/+03ynTuvC1p51Ts/fcp/umnZJ13Xp7uPWbMGBYtWsR//vMfFi5cuG1ls5tuuola&#10;tWoxdOhQli5dSlZWFh07dqRmzZrMnDmTH374gVq1alG5cuV9qltBkegW949AB+DFHY7fA4zwfT9x&#10;i7mKiEi+y1iwALM29+VOAUqOGMGGM85gS2bmXt/70ksvZeHChWRlZdGgQQPatWvHkiVLGDp0KEOH&#10;DmXOnDk8/vjjAMyePZvatWtz8skn06JFi0KTtCHBidv3/fGe59XMeczzvMpAC9TaFhEpdMyaNbt9&#10;3/njD5yNGyEPiTvbzz//zJdffsnUqVOx1rJmzRpKlixJ165deeihh1i/fj1nnHFGnu9f0CVj5bQL&#10;gJd93497kfTYmq0pJ1Xjjpfql9pUv9RWUOu3/uCDd/v+1uOOo1yNGmSUL7/b83KrnzGG9PR0jj76&#10;aOrVq8e5557LihUreO2118jIyOD3339n9OjRZGVl0axZM6688kpKly5N+fLlC9zntS/x5FfizrlQ&#10;+hnAwL25OBUXm9ci+alN9Uttql/yFKtVi2I1a5Ie2ypzRxu6dGHt+vWwfn2u78Ou65eVlcWGDRv4&#10;888/GT9+PC+88ALr16/nyiuvZPPmzSxatIiOHTuSlpbGhRdeyLJly6hZsyZDhw6lePHi1KhRY7/V&#10;c1/sxSYjucqvxJ2zdV0b+DmfyhURkXyUVakSa557jnKXXILz++/bjltjWN+vHxsaNMjzvYsVK8bT&#10;Tz+9y/d79Oix07G2bdvStm3bPJdZECU8cfu+vwholOP1MYkuU0REkmeD67J14kSKff89afPnYytU&#10;YPPxx7PpsMMIixVLdngpT7uDiYjIfpdVtSpZVatC8+bJDqXQ0cppIiIiKUSJW0REJIWkROK24c4r&#10;8IiIiBRFKZG4w8G3Yn/8LtlhiIiIJF1KJG4W/0Q4tBfhqIewK/ZtdxkREZFUlhKJ2+l1P9Q8Ajvz&#10;I8K+XQjf8rGbs5IdloiISL5LicRtDj8Kp/eDmCtuguIlsP83hvDurtgvP8PauFdOFRERSXkpkbgB&#10;jOPgNGmFM+hJzJnnwcq/CUfeR/jI3dgli5MdnoiISL5ImcSdzZQqjXPh1Tj9R0C9E+D7bwgHdCMc&#10;+zR23a63khMRESkMUi5xZzNVq5PWvR/OTX3hgKrYyRMJ+/ybcOo7mj4mIiKFVsom7mzm2JNw7hmB&#10;ueBK2LIF+9JIwoG3YBfMTXZoIiIi+13KJ24Ak56B07pj9Py7UUv4bSHhA70Jn7ofu/yvZIcnIiKy&#10;3xSKxJ3NlKuAc1V3nN4PQq3a2FmfEN7dhfC/Y7FZm5IdnoiIyD4rVIk7m6lVG6fX/ZirboaSpbET&#10;xhL2vQE76xNNHxMRkZRWKBM3xKaPNWqBM2gk5qzzYfVKwqfuJ3yoD/a3hckOT0REJE8KbeLOZkqU&#10;wjn/Cpx7HoPjToZgDuGAHoQvjcSuXZ3s8ERERPZKoU/c2UyVaqTd2Aene384sBp26juEd3UmnDwR&#10;u1XTx0REJDUUmcSdzdRrgNNvOMa7BmyIHfs04cCbsd9/k+zQRERE9qjIJW4Ak56O06p9NH2s6Zmw&#10;dDHhw33ZOvI+7F/Lkh2eiIjILhXJxJ3NlC2Pc/mNOHc9BEfUgS8/I7y7K+H/jcFu2pjs8ERERHZS&#10;pBN3NlPzCJzbh2Cu7QmZZbFv+YR9byD8/CNNHxMRkQJFiTvGGIPT8HScgU9gzvFgzT/Y0Q8R3n8n&#10;dvFPyQ5PREQEUOLeiSlREqfDpTgDHof6p8CP3xEOuoXwhcewa/5JdngiIlLEKXHvgqlclbQbeuPc&#10;MhAOOgT78XvR9LEP3sRu2ZLs8EREpIhS4t4DU+c4nLuHYTpdDwbsK88QDuiOnfdVskMTEZEiSIk7&#10;DiYtDadlG5xBT2FOPwuWLSF8tB9bHxuE/fP3ZIcnIiJFSHqyA0glpkxZzKU3YE8/m3Dc0/DNTMJ5&#10;X2Jatcec42FKlEx2iCIiUsipxZ0H5pBaOLfei7n+dihbHvvO64R9uhB+NgUbhnt3L2P2vvwc1+Tl&#10;ehERSV1qceeRMQZzUhPssSdhJ72OffcN7LOPYKe+jdPpeqhWbZfXbt5sWbBgDZMnL2Hu3BXUq1eR&#10;Fi0OpnbtMmRk5J6Ic16zatUmGjY8kHnzVjJ//sq4rhcRkcLBpMACI3bp0qXJjmGP7PI/sa8+h509&#10;HYDSrdqyofUFmHIVtjtv82bLhAm/0q3bJ+T86I2B4cOb0LbtITsl35zX1K1bkTZtajJ06FdxX58I&#10;1apVIxW+L3ml+qU21S+1qX7ROUCuP8zVVb6fmEpVcDrfgXPrYKh+KOven0DYpzPhpPHYLZu3nbdg&#10;wZqdkjaAtdCt2ycsWLBmp3vnvObCCw/fKWnv6XoRESk8lLj3M+Meg9PnESrc0AvS0rGvPUfYvxt2&#10;ziwAJk9eslPSzWYtTJmyZKfj2ddUq1aKxYvX7vX1IiJSeCT8GbfneQ2BIb7vN/c8rzIwCigPpAGX&#10;+76/MNEx5DeTlkbmuRfwT+1jsG++jP3oHcLhAzDHnMifc+vv9tq5c1dijNm2RroxhrlzVwBQtWqU&#10;uPfmehERKVwS2uL2PO82okRdPHbofmCM7/vNgL7AUYksP9lM6TI4F/8b5+5hcNSx2Dmz6Muz9D7q&#10;azLTN+d6Tb16FbZLutZa6tWrCMCyZeupUSNzt2XueL2IiBQuie4q/xHokON1Y6C653nvAxcDUxNc&#10;foFgDq6Jc8tAnC53srVMRTofNp+pp7/FhdV/xvC/JGsMNG9+8E7Xt2hxMMbA0qVR4t7VDLBdXS8i&#10;IoVHQhO37/vjgZwLex8KrPB9vxXwK9ArkeUXJMYYTINTSR/wON8f2YbMtM08dOxM3mz0PvXL/40x&#10;MGJEU2rXLrPTtbVrl2H48CYYA6+++hN33FF/p+S9u+tFRKTwyO953MuBCbGvJwCD8rn8pMsoXQK3&#10;x3X8PLsV9vXnOJ6vebPRB/xTpwllmpTMdSpXRoahbdtDcN02TJmyhJUrN/Hss8357ruVzJ+/inr1&#10;KtC8ueZxi4gUBfmduD8GzgFeAk4D5sVzUbXdLGZSkO0u7po1DyY871Q2zv2S1aMeodz3n2AGzCbz&#10;omso0+FiTEaxXK6Bli1rE4YhjhN1lmR/nf06P6Xq9yVeql9qU/1Sm+q3a/mduG8FRnue1wX4h+g5&#10;9x6l4kT8uBcQOKAa9o4hmE8+wI5/kX/+8xj/vP0ajncNHHdygV3SVAskpDbVL7WpfqltLxZgyVXC&#10;E7fv+4uARrGvFwNnJrrMVGOcNMxprbEnNsZOGIed8hbh44Ph6Po4na7FHHRIskMUEZECQguwFCCm&#10;VCbORdfi9BsOR9eH774ivKcb4Sujset3P39bRESKBiXuAsgcdAjOzf1xut4FFStjP/hvtPvYtEnY&#10;cGuywxMRkSRS4i6gjDGY4xvi3PM4puPlkLUJ++LjhIN7Yn/4LtnhiYhIkihxF3AmIwPn7AtwBo3E&#10;nNIcFv9MeH8vwlEPYlf8nezwREQknylxpwhTvhLONT1wet0Phx6JnTmNsG8XwomvYLM2JTs8ERHJ&#10;J0rcKcYcfhTOnQ9gruwGJUpi33yJ8O6u2C8/1RrlIiJFgBJ3CjKOg9P4DJxBT2Jad4BVKwhHDiF8&#10;uC/2t1+SHZ6IiCSQEncKMyVL4VxwFU7/EXDMiTD/W8IBNxO+/BR23ZpkhyciIgmgxF0ImKoHk9bt&#10;bpxud0OVg6IFXPp0Jpz6tqaPiYgUMkrchYg55kSc/sMxF1wFW7ZgX3qScGAPbDA32aGJiMh+osRd&#10;yJj0DJzWHaLn341bwm+/ED7Ym/DJodjlfyY7PBER2UdK3IWUKVcB58ruOL0fgsNc7OzphH1vIPzv&#10;y9hNmj4mIpKqlLgLOVPrSJw7hmKu6QGlMrETxhHe3YXwi080fUxEJAUpcRcBxnFwTmkerb529gWw&#10;ehX26fsJH+yNXfxzssMTEZG9oMRdhJgSJXE6Xo5zz+Nw3MmwYB7hoFsIxzyBXbM62eGJiEgclLiL&#10;IFPlINJu7INz8z1Q9WDsR+8S9vk34YcTsVs1fUxEpCBT4i7CTN36OHcPw1x0DViw454mHNAd+/03&#10;yQ5NRER2QYm7iDPp6ThntMcZ/CSm6Znw+6+ED/dl6xP3Yv9aluzwRERkB0rcAoApUw7n8htx7noY&#10;jjgavppBeHdXwvFjsBs3JDs8ERGJUeKW7Ziah+Pcfh/muluhTDns2340/3vGVE0fExEpAJS4ZSfG&#10;GJyTT8MZ+ASmzUWwdjX2mYcJ7++FXfRTssMTESnSlLhll0zxEjjtL8EZ+AQ0aAQ/fk84+BbCFx5j&#10;66oVyQ5PRKRIUuKWPTIHHEhal144twyEajWwH7/H79d3JHz/TeyWLckOT0SkSFHilriZOsfh9H0U&#10;86/rMcbB+s8Q3tMNO/fLZIcmIlJkKHHLXjFpaTgt2lB11BuYZmfDH0sJh/Vn62ODsH8uTXZ4IiKF&#10;XnqyA5BKITMbAAAgAElEQVTUlFa2PM4lXbCnn0U4bjR8M5Nw7peYM9ph2niYEqWSHaKISKGkFrfs&#10;E1O9Fk7PQTid74ByFbCT3iDs04Xw0w+xYZjs8ERECh0lbtlnxhjMCY2j6WPtLoYN67DPDSMccjt2&#10;4YJkhyciUqgocct+Y4oVx2nbCWfASMxJTWHhAsJ7byV8bhj2n5XJDk9EpFBQ4pb9zlSqjHP9bTi3&#10;3gvVa2E//ZCwT2fCSW9gt2xOdngiIilNiVsSxrj1cPo+jLmkC6SnY197nrDfTdhvv0h2aCIiKUuJ&#10;WxLKOGk4zc7GGfQUpmVb+HsZ4YiBbB12D3bZb8kOT0Qk5ewxcXue1yA/ApHCzZTOxOl0Hc7dw6HO&#10;cTB3NmH/mwj9Z7Dr1yU7PBGRlBFPi/ulhEchRYY5uAZOjwE4N/SGCgdg338zev798XuaPiYiEod4&#10;FmD51vO8i4FPgLXZB33fj2uXCc/zGgJDfN9v7nne8cBEIHuO0Ejf91/dy5glxRljoP4pOPUaYN/7&#10;P+zbr2JfeAz70bs4na7DHFEn2SGKiBRY8STu9sCFOxyzQNqeLvQ87zbgMv6X8E8AHvJ9/5G9CVIK&#10;J5NRDHOuh23UEvv689jPPyIcegfmlGaY86/AlK+U7BBFRAqcPSZu3/dL7MP9fwQ6AC/GXp8A1PY8&#10;7zzgB6C77/t6wFnEmQqVMNf2xDY7m3DsKOyMqdivZmDOuRDTqj0mo1iyQxQRKTD2mLg9z3OAW4B6&#10;wE3AjcD9vu9v3dO1vu+P9zyvZo5DnwOjfN//yvO83kB/4La8BC6FjzniaJy7HsRO/xA7/sXozyfv&#10;41x4NRzfMOpiFxEp4uIZnPYAcCzQMHb+WUBeu7r/z/f9r2JfjweOz+N9pJAyThpO0zNxBj2JadUe&#10;VvxF+MS9hI/2wy5dnOzwRESSLp5n3C2BBsBs3/f/8TzvTODrPJY3yfO8G33fnxW77+x4LqpWrVoe&#10;i0uuVI07Xgmv38192Xz+Zawa9TAbZ39KeE93MttcSLmLr8cpUzaxZaPvX6pT/VKb6rdr8STuzb7v&#10;h57nAeD7/ibP87bksbwuwAjP87KAZcD18Vy0dGnq7fNcrVq1lIw7XvlWv7Ri2H/fgfPtLEJ/NGv/&#10;O461k9/GnHcppmkrjLPHMZJ5ou9falP9Upvqt/vEHk/inut5XlcgzfM8l+h5d9wtbt/3FwGNYl9/&#10;BTSJ91oRiE0fO+4knKOPx374X+xEHzvmCexH7+B0uh5Tu+4ur7PW5nO0IiKJFU/i7k70TPtAYDow&#10;CeiWyKBEcmMyMjBnnY89pTn2jRewn00mfOBOzElNMRdcialYGbN5MyUWLKDY5Mmkz53Llnr1yGrR&#10;go21a2MzMpJdBRGRfRbPdLDVwDX5EItIXEz5ipirb46mj40bhf3iY+w3n+Oc2ZHMrHTK9LgFE2tp&#10;F584kVJDh7J2+HDWtm2r5C0iKS+e6WBVgGFAK2Az8DbQ0/f9VQmOTWS3zGEuTq/7sTOmYN94gXDi&#10;ONau30T6geUouWwV2ZPHjLVkduvGFtdlQ93cu9VFRFJFPNPBRgE/AycDTYGVwFOJDEokXsZxcBq1&#10;xBk4khKVD2VriQyWNzicv04+kqwy/1s7yFhLsSlTkhipiMj+Ec8z7kN932+f4/WtnufNSVRAInnh&#10;lCpN2eWbKD/tO1bVqc7GA8vzR5OjyVz8F2UXLCVt81bS587VgDURSXnxtLiXep5XK/uF53nVgd8T&#10;F5LI3rPWsqVePTLWb6Ly7J84YOYPpK/bxNqaVVh2ej3W1KzM5rpHK2mLSMrbZYvb87wJRJuJVAa+&#10;9jzvA2Ar0Bz4Nn/CE4lfVosWlBo6FGMtJf9eTYmPv2PtoZX554hqrKpbA2fpXJj/LeaoY5MdqohI&#10;nu2uq/y1XRx/KxGBiOyrjbVrs3b4cDK7dcNYi7GWMgv/pOTSlSy/4nyylvwID/WBExrhXHg1plKV&#10;ZIcsIrLXdpm4fd//T87XnueVSnw4InlnMzJY27YtW1yXYlOm/G8ed/PmhLVr4yz5hXDcKJj9KeG3&#10;szCtO2DOugBTvHiyQxcRiVs808F6AIOB7J9uhjj34xbJbzYjgw1167Khbt2dBqKZQ4/EuWMo9vOP&#10;ov2/J76Cnf5htHjLSU21+5iIpIR4BqfdApwClI39KRP7W6RAy20gmjEG55RmOANHYs65ENaswo56&#10;kPCBO7GLf0pClCIieyee6WA/+L6vwWhSqJgSJTEdLsM2aUXoPwtfzyAcdAum6ZmY8y4FCvfORCKS&#10;uuJJ3I95nvcK8B7RymkA+L7/QsKiEsknpnJV0rr2xn73dbR86rRJ2FmfsObSztj6jTHp8fwXERHJ&#10;P/H8VOpKtMFIzsFpFlDilkLDHH08zt3DsB+9g/3vy6x6+iE4yMfpdC3m6PrJDk9EZJt4EncN3/eP&#10;THgkIklm0tMxLdtiTz6Nku+PZ9274wkf6QfHN8TxrsFUrprsEEVE4hqc9ovneXrgJ0WGKVOOijf2&#10;xunzCBx5NHz9OeHdNxC+8QJ244ZkhyciRVw8Le4NwFzP874ANmUf9H2/XcKiEikATI3DcG67Dzvr&#10;E+xrz2HfeQ372WTM+VdgGjbT9DERSYp4EvfrsT8iRY4xBnNSU+yxJ2PffR076Q3sM49gp76D0+k6&#10;zKF6iiQi+WuPiXvHFdREiiJTvDim/cXYxi0JX3suWn3t3lsxjVpiOl6GKVsh2SGKSBERz8ppa4hG&#10;kW/H930twiJFjjngQNI698LO/zaaPjb9A+yXn2LaXIRp0QaTnpHsEEWkkIunq7xejq+LAR2JdgkT&#10;KbLMUcfi9H00mvf95kvYV5/Dfvwejnct5pgTkh2eiBRi8XSVL9rh0FDP8z4HHkxMSCKpwaSlYZqf&#10;gz2pCfa/L2Onvks4/B445kSci67FHKjJGCKy/+31slCe5x1FtCCLiAAmsyzm4s7Y086Kdh+bM4vw&#10;u68xZ7TFnHsRpqQ21hOR/Wdvn3Ebou7y2xMZlEgqMtUPxek5CL78jPDVZ7GTxmNnTMV0uBxzanOM&#10;E8+yCSIiu7e3z7gtsMr3/dUJikckpRlj4IRGOMecgH1vfDT3+/loKVWn03WYw9xkhygiKW6XTQDP&#10;82p4nleDKFln/wEoHzsuIrtgihXHadMp2j70pKawcAHhfbcRPvsIdtWK3K/Rgi4iEofdtbjnESXr&#10;nD9NLFCSKOGnJTAukULBVKyMuf42bLNzCMc9jf1sCvbLGZhzPcwZ7XCAEgsWUGzyZNLnzmVLvXpk&#10;tWjBxtq1sRmaWiYiO9tl4vZ9v0zO157nGaA3cGvsj4jEydSui9PnYewn72PHj8G+8R/sx5MoeUhd&#10;yg1+AMdGHVrFJ06k1NChrB0+nLVt2yp5i8hO4hpV7nnewcAYoAzQ0Pf9BQmNSqQQMk4a5rSzsCc0&#10;wU4Yi538Fuv+WsbWEw+n/He/krEu2grAWEtmt25scV021K2b5KhFpKDZ4zBXz/M6At8As4FTlbRF&#10;9o0pnYnT6TrKHdmQ4n+tZmPlcixrWpeVdaoTpkf/JY21FJsyJcmRikhBtMsWt+d5JYFhwLlAJ9/3&#10;P8i3qEQKOWMMxX/8hTJf/MDGKuVYWecQ1tY6kPXVKlIuWELp35aTPncuxhis3WnFYREpwnbXVf4l&#10;UJMoeR/red6xOd/0ff/hRAYmUphZa9lSrx7FJ06k5J//UOLv1aypdSCrD6/KymMPZW3NypSodXCu&#10;SVvJXKRo213i/hyYAVSN/clJPzVE9lFWixaUGjoUYy0mtJT9aRmlflvOP0cdzPqDK7H5xy8wox7C&#10;nH8FTplyGn0uIsDuR5VfmY9xiBQ5G2vXZu3w4WR264aJtaDTN22m4reLcC64nLVL5mNnfoT9egbF&#10;ah5NuceexdkaAhp9LlKU7fVa5XvL87yGwBDf95vnOHYxcKPv+40SXb5IQWUzMljbti1bXJdiU6b8&#10;ryXdvDkba9fGSUvDfvohvPocG3/4imVNj6b8979R8o9VGDT6XKSoSmji9jzvNuAyYG2OY/WBqxNZ&#10;rkiqsBkZbKhblw116+707NoApkkrysyaw9YJ41hz6IEsP+Fwiv+9mgrf/UrG2o3bRp8rcYsUHYne&#10;9eBHoEP2C8/zKgGDgO4JLlck5exqIFqx7wPKz19C1Y/nUeLPf9h0QFmWNTmalUcfQpietm30uYgU&#10;DfHM4/7S87xrPc/b670Jfd8fD2yJ3ccBRgO3AOvYfilVEclF9uhzgIx1m6g860cO+OIH0jdsYu2h&#10;Vfi9WT3WVi1HuHVLkiMVkfxi9jStxPO8RsC/gTOB14GRvu/Pi7cAz/NqAmOBbsBzwF9E653XAZ71&#10;ff+WPdxCI9ilSFs/bRolmzXbNoANwBrDmkOrsPrIg7DpaWTUqk35zrdSol6DJEYqIvtZrg3cPSbu&#10;bJ7nlQcuBnoCS4Hhvu+/Gsd1NYFxvu+fusOxsXEOTrNLly6NK8aCpFq1aqRi3PFS/fKP2byZzAkT&#10;tht9DlHyXv3gUNas+xM7I1plzZzYBHPBVZhKlXd7z4JUv0RQ/VKb6hedwy4Sd7xrlZcnGmR2DfAP&#10;4AOXe57X1vf9y+O4hVrNInm0x9HnGRnYFucSjn0aO+sT7LczMa3Px5zVEVOseLLDF5H9bI+J2/O8&#10;l4BzgIlAF9/3P4sdHwn8uafrfd9fBDTa0zGRgizZq5XtdvS5MVCrNk6v++Hzjwhffz7axGT6BzgX&#10;XgUnNNbgNZFCJJ4W9zzgZt/3/8p50Pf9LZ7nNU5MWCLJt3mzZcGCNUyevIS5c1dQr15FWrQ4mNq1&#10;y5CRkbxEaK3dLrZVqzbRsOGBzJu3kvnzi1G/Tg86HjmTil+/S/jU/eAeg9PpWkz1WkmLWUT2n7ie&#10;cXuedw7QGtgKTPB9Pz+3LdIz7gKosNevfPlKPPvsV3Tr9gk5/4sYA8OHN6Ft20OSlrw3b7ZMmPAr&#10;3bp9Qt26FWnTpiZDh361U5zP3OfScuXbmDlfgHEwp7fGtL8Ek1m20H//VL/Upvrt/hl3PNPB+gEP&#10;ET3bXg885Xlet72OVCSFzJq1ZKekDWAtdOv2CQsWrElOYMCCBWu2xXbhhYfvlLQhivOaOwOClt1x&#10;uveHA6thp75DeFdnwskTsZo+JpKy4lmA5TLgFN/37/Z9vw/QEOiS2LBEkmvSpEU7JcNs1sKUKUvy&#10;N6AcJk9egrVQrVopFi9eu8c4Tb0GOP2GY7xrwIbYsU/zx02XYL//Jn8DF5H9Ip7EvRzI2bxYRY4l&#10;TEUKG2MM3377927PmTt3ZVIGfBljmDt3BQBVq0aJe3ey4zTp6Tit2uMMehLT9Ew2L/6Z8OG+bB15&#10;H/avZfkRuojsJ/Ek7lnAm57ntfE87yzgRWCx53kdPc/rmNjwRPKftZZjjz1gt+fUq1chKaPMrbXU&#10;q1cRgGXL1lOjRuZuz98xTlO2PM7lN3LgIy/AEXXgy88I7+5K+H9jsJs2JjR2Edk/4kncRwOZRAuv&#10;3AEcDFQEbgJuTFxoIsnTunVNdtWgNgaaNz84fwPKoUWLgzEGli6NEnde4ix2ZB2c24dgru0JmWWx&#10;b/mEfW8g/PyjpE57E5E92+N0sOztOD3PSweM7/ubEx6VSJKdeOLBDB/eJNdR5SNGNKV27TJJi612&#10;7TLbYnv11Z+44476uY4q31OcxhhMw9Oxx52Mfed17HvjsaMfwk59B+df12FqHJ4PtRGRvRXPWuVV&#10;gP8ALYgS/UfApb7v59dYfU0HK4CKQv0WLVrCggVrmDJlCXPnrqRevQo0b578edzwvznmU6YsYeXK&#10;aB73d9+tZP78VXHFmdv3z/61jPDVZ+GrGWAMpkkrTIfLMGXK5UeV9qui8O9T9Utd+bHk6WPADOBf&#10;QBrRZiEjgfZ7E6hIqsnIMNStW5a6dcsmfeW0HeUW25lnHrRPcZrKVUm7oTf2+28Ix43CfvwedtZ0&#10;TLtOmGbnYtLjWiFZRBIsnv+JtX3f93K87ud5Xty7g4kUBgUpae8oZ2z7I05T5zicu4dhp76D/e9L&#10;2FeewU57D+eiazF16+/z/UVk38QzOC3D87wS2S9i+3IX3J9iIrLPTFoaTss2OIOewpx+FixbQvho&#10;P7Y+Ngj75+/JDk+kSIunxT0O+MDzvOdir68CXktcSCJSUJgyZTGX3oA9/WzCcU/DNzMJ532JadUe&#10;c46HKVEy2SGKFDl7bHH7vj8QeAY4EzgLeB64J7FhiUhBYg6phXPrvZjrb4ey5bHvvE7YpwvhZ1Ow&#10;YZjs8ESKlN22uD3PywCK+77/HPCc53nHAPN931dXuUgRY4zBnNQEe+xJ2EmvY999A/vsI9ipb+N0&#10;uh5T68hkhyhSJOyyxe15XnWiLT3b5DjcB5jjeV61RAcmIgWTKV4cp93FOAOfwJzQGH4OCO/tSfj8&#10;MOw/K5Mdnkiht7uu8geAZ33fH5d9wPf9i4AxwP2JDkxECjZTqQpO5ztwbh0M1Q/FTv+QsE9nwknj&#10;sVu0TpNIouwucdfzfX9ILsfvBRokKB4RSTHGPQanzyOYSzpDWjr2tecI+3fDzpmV7NBECqXdJe6s&#10;3A76vh8C2o1ARLYxaWk4zc7BGfwkpvm58NfvhMMHsHX4AOyy5G2BKlIY7S5xr/Y8r9aOBz3POxzY&#10;kriQRCRVmdJlcC7+N87dw+CoY2HOLML+NxG++hx2w/pkhydSKOxuVPlDwATP87oBnxIl+VOAYUTd&#10;5SIiuTIH18S5ZSB8NYPQfybawGTGFEzHyzGntsA48az9JCK52eX/Ht/3JxIl6NHAOmAN8Dhwr+/7&#10;Y/MnPBFJVcYYTINTcQY8jml/CWzcgH1+OOF9t2F/mp/s8ERS1m7ncfu+/zLwsud5FYHQ9/1V+ROW&#10;iBQWplhxTJuLsI1aYl9/HjtzGuGQ2zGnNMecfzmmfKVkhyiSUuLa7sf3/RWJDkRECjdT8QDMdbdi&#10;m51DOO5p7Iwp2K8+w5zrYc5oj8nISHaIIilBD5pEJF+ZI4/GueshzGVdIaMY9o0XCPt1xX79eYHe&#10;hU2koFDiFpF8Z5w0nNNaR9PHzmgHK/4ifHww4aP9sb//muzwRAq0PXaVe55XY4dDFljv+/7yxIQk&#10;IkWFKZWJueha7GmtCceNhu++IrynG6b5uZi2nTClMpMdokiBE0+LezqwEPgW+Br4BVjqed4Sz/Ma&#10;JTA2ESkizEGH4NzcH6frXVCxMvaD/0a7j02bhA23Jjs8kQIlnsT9AXCV7/vlfd+vCHhEW3u2AR5J&#10;YGwiUoQYYzDHN8S553FMx8shaxP2xccJB/fE/vBdssMTKTDiSdzH+b7/QvYL3/dfB07wff8roFjC&#10;IhORIslkZOCcfQHOoJGYU5rD4p8J7+9FOOpB7Iq/kx2eSNLFk7jTPc+rl/0i9nWa53klAM3fEJGE&#10;MOUr4VzTA6fX/XDokdH8775dCCe+gs3alOzwRJImnnncvYCpnufNI0r0RwIXA/cA4xMYm4gI5vCj&#10;cO58APvZZOwbL2DffAn7yfs43tVQ/1SMMckOUSRf7bHF7fv+20BtoufZQ4A6vu9PBgb5vt83wfGJ&#10;iGAcB6fxGTiDnsS07gCrVhCOHEL4cF/skkXJDk8kX+0xcXue5wDXAjcDdwI3eZ6X7vv+mkQHJyKS&#10;kylZCueCq3D6j4BjToT53xIO6E748lPYdfqRJEVDPF3l9wHHAY8SJfrrgQeAHvEU4HleQ2CI7/vN&#10;Pc87Gngq9tYPwLWx/b1FROJmqh5MWre7sXNmEb7yDHbKW9gvpmHaX4I5rXWywxNJqHgGp50FtPV9&#10;//98338DaA+cHc/NPc+7DRgFFI8dGgz08n2/KWCAtnsfsohIxBxzIk7/4ZgLroItW7AvPUk4sAcb&#10;58xOdmgiCRNP4nZ839+c/cL3/U3A5t2cn9OPQIccrzv6vj/d87xiQFXgn7gjFRHJhUnPwGndIXr+&#10;3bgl/PYLf/X6N+GTQ7HL/0x2eCL7XTxd5V97nvcI8FjsdVeiVdT2yPf98Z7n1czx2saWUP0AWAV8&#10;s5fxiojkypSrgLmyO/b0c0h/43myZk/HfvsF5qyOmNbnY4oX3/NNRFJAPIm7KzAc+JSoe3sScFNe&#10;C/R9fzFQ2/O8a4hGql+5p2uqVauW1+KSKlXjjpfql9oKbf2qVcOe2pT1U99l1XPDCSeMw5kxhfLX&#10;3EzJJmcUmuljhfb7F6P67doeE7fv+6vZIbl6nlcX2Os9uj3PexPo6fv+j8AaIK5FiJcuXbq3RSVd&#10;tWrVUjLueKl+qa0o1O+fo46Hex7HvP0qW9//P5YPuRNqj8HpdD3mkFrJDnGfFIXvX1Gv3+4Sezwt&#10;7tx8BpTNw3VDgOc9z9sErCeaZiYikhCmRElMx8uxTVoR+s/ANzMJB/bAnHYmpv2lmDJ5+TEmklx5&#10;Tdxx9zX5vr8IaBT7+jOgSR7LFBHJE1PlINJu7IOd9xXhK6OxH72L/eJjTLtLMM3OxqSlJTtEkbjF&#10;M6o8N3a/RiEikg9M3fo4dw/DXHQNWLDjniYc0B37vcbJSurIa+IWEUlJJj0d54z2OIOfxDQ9E37/&#10;lfDhvmx94l7sX8uSHZ7IHu2yq9zzvDXk3rI2QKmERSQikg9MmXKYy2/Enn424bhR8NUMwjmzMWd2&#10;wJx9PqZEyWSHKJKr3T3jrreb90RECgVT83Cc2+/DfvEx9rXnsW/72E8/xJx/Babh6YVm+pgUHrtM&#10;3LFBZSIihZ4xBnPyadjjTsa++zr23TewzzyM/eidaPpYzcOTHaLINnrGLSISY4qXwGl/Cc7AJ6BB&#10;I/jxe8LBtxC+8Bh29apkhycCKHGLiOzEHHAgaV164dwyEKrVwH78HmGfLoTvv4ndsiXZ4UkRp8Qt&#10;IrILps5xOH0fxfzrejAG6z9DeE837Nwvkx2aFGFK3CIiu2HS0nBatImmjzU7G/5YSjisP1sfG4T9&#10;s/AuyykFV15XThMRKVJMZlnMJV2wp59FOG50tHzq3C8xZ7TDtPEwJTRLVvKHWtwiInvBVK+F03MQ&#10;Tuc7oFwF7KQ3ouffn36IDcNkhydFgBK3iMheMsZgTmiMM/AJTLuLYcM67HPDCIfcjl24INnhSSGn&#10;xC0ikkemWHGctp1wBozEnNQUFi4gvPdWwueGYf9ZmezwpJBS4hYR2UemUmWc62/DufVeqF4L++mH&#10;hH06E056A7tlc7LDk0JGiVtEZD8xbj2cvg9jLukC6enY154n7HcT9tsvkh2aFCJK3CIi+5Fx0nCa&#10;nY0z6ClMy7bw9zLCEQPZOuwe7LLfkh2eFAKaDiYikgCmdCam03XYpq0JXxkFc2cTfv81pkUbTJtO&#10;mFKlkx2ipCi1uEVEEsgcXAOnxwCcG3pDhQOw778ZPf/++D1NH5M8UeIWEUkwYwym/ik4Ax7HnHcp&#10;bNqIfeExwntvxf74fbLDkxSjxC0ikk9MRjGccz2cQU9iGp4Oi34kHHoH4TMPY1ctT3Z4kiKUuEVE&#10;8pmpUAnn2p44dwyBGodjZ0yNVl97+1Xs5qxkhycFnBK3iEiSmCOOxrnrQczlN0Kx4tjxLxL2uxH7&#10;1QystckOTwooJW4RkSQyThpO0zOj7vNW7WHFX4RP3Ev4aD/s0sXJDk8KICVuEZECwJQqjeNdg9Nv&#10;BNRrAN99TXhPN8Jxo7Dr1iY7PClAlLhFRAoQc1B1nG79cG7sCwcciP1wQjR97KN3seHWZIcnBYAS&#10;t4hIAWOMwRx3Ek7/xzDnXwGbN2PHPEE46BbsgnnJDk+STIlbRKSAMhkZOGedjzNoJObUFvDrQsIH&#10;7mT50N7YFX8lOzxJEiVuEZECzpSviHP1zTh3PgC1arN+2nuEfbsQThyHzdqU7PAknylxi4ikCHOY&#10;i9Prfir26A8lS2PffJnw7q7Y2dM1fawIUeIWEUkhxnEofUYbnIEjMa07wqoVhE8OJXyoD/a3X5Id&#10;nuQDJW4RkRRkSpbCueBKnHseg2NPgmAO4YCbCV96Ert2dbLDkwRS4hYRSWHmwGqk3dQXp3s/OPAg&#10;7NS3o+VTp7yN3arpY4WREreISCFg6p2A02845sKrIdyKfflJwoE3Y4M5yQ5N9jMlbhGRQsKkZ+Cc&#10;eV40faxJK1i6mPDBu9j65BDs8j+THZ7sJ+mJLsDzvIbAEN/3m3uedzwwHNgCbAIu931fkxFFRPYj&#10;U7YC5oqbsKefRThuFMz+lPDbWZjWHTBnXYApXjzZIco+SGiL2/O824BRQPa/kkeBrr7vtwDGA70S&#10;Wb6ISFFmDj0S546hmGtugdKZ2ImvRPO/Z07T9LEUluiu8h+BDjleX+T7fvYDl3RgQ4LLFxEp0owx&#10;OKc0i6aPnXMhrFmFHfUg4QN3Yhf/lOzwJA8Smrh93x9P1C2e/foPAM/zGgFdgUcSWb6IiERMiZI4&#10;HS7DGfAE/H97dx4mRXX1cfx7a0CQTcUFHRVJNLhAjEsUAwoCGhElhKgXxO1NIojii0ZFZVEWIahR&#10;UJYgrqiJxqNvMGo0GgWNEkUhQFiiuEIEQaKCCMpW9f5RPWYYB5ylu2uq5/d5Hh6qq7tunfP0zJy+&#10;t7ruPeI4eHsx4agrCB+cRLRubdLhSSW4XA+XeO8PAB42s7aZxz2BQUB3M1tagSY0niMikmVfzZ3F&#10;Z3feypZl7+EaNmaXcy+iUdczcXVy/tUnqThX3s68vkPe+3OBvsCJZramosetWLEid0HlSHFxcSrj&#10;rijll27KL92ykl+z/YkG3YJ76RmiJx5izZRbWPPEIwS9+uAOOyI7gVaR3r/4NduTt9vBvPcBcDvQ&#10;CJjmvZ/uvR+Wr/OLiMi2XJ06BJ27EYy6A9e+C6z8kHDc9WydNJpo9cqkw5PtyHmPOzMc3jbzcPdc&#10;n09ERCrHNd4Fd94lmdvH7oR5swgXzsGd/FNc17Nw9XdOOkQpRROwiIgIAK75dwkGjsH1HQhNdiV6&#10;5rH49rHXZuj2sRpEhVtERL7mnCM45gSCkZNxp/eC9V8Q3TOO8KZriD54O+nwBBVuEREph6tXj6B7&#10;bwkZ2cEAABG6SURBVIKRk+DotvDum4S/vopw6niizz9LOrxaTYVbRES2y+3RjKJ+1xJcOQqKmxPN&#10;fD5efey5aURbNicdXq2kwi0iIt/KHXI4wXW34Xr3g6CI6NH7CEcMIFowJ+nQah0VbhERqRBXVETQ&#10;sWu8+ljHrrDqI8LxI9g6fiTRqsK977qm0RQ5IiJSKa5RE1zvfkTtM6uPLZhNuHge7qRuuNN64nZu&#10;kHSIBU09bhERqRK3XwuCK0cR9LsWdm1K9Oy0+PaxmS8QhWHS4RUsFW4REaky5xzu6LYEIyfhuveG&#10;L9cTTb2d8Marid57K+nwCpIKt4iIVJvbqR7B6b3i5UOPOQHeX0I4ZiDhveOI1nyadHgFRYVbRESy&#10;xjXdk6DvQIKBY2D/7xC9OiO+feyZ/yParNvHskGFW0REss61bEUwdCzuvEugbl2iP95POPxSovmv&#10;V2r6VOdcuY/L7q9N9K1yERHJCRcU4dp3ITr6eKInHyaa8WfCiaOg1ZEEPfvg9tmv3OM2bNjIokWf&#10;M336chYu/JTWrZvSpk0zVq3awJYtEUuWrOGddz7n8MOb0qnTvrRs2Zi6dWtPIVfhFhGRnHING+F6&#10;9SFqfwrhI3fDormEI/4X1/F0XLdeuAYNv37t5s0R99//T/r3f4mSjvlTTy2ldeum9O79PYYMmfX1&#10;/qefXspNN81l/Pjj6dZt/1pTvDVULiIieeGKmxNcPoKg/2BouifR838iHNqP8OXniMKtACxZsm6b&#10;ol3irLMO3KZol4giGDDgFZYsWZenLJKnwi0iInnjnMMdcRzBiIm4HufBpo1ED0wkHH0V0TuLmT59&#10;+TeKc3FxA5Yt++Ib+0tEEcyYsTz3wdcQGioXEZG8c3V3wnU9i+hHnYj+eD/Ray8S3nQtP+Qw9q5/&#10;ECu/+u/sa3vvHRfuHVm48DOcc7Vi3XD1uEVEJDFut90JfnkFwbU3wwEHcSyLebH9n7n0wEXUC+Lh&#10;85UrN9C8eaMdttO69W61omiDCreIiNQA7sBDCAbfwkcn92H91jpcffACXmj/NKc0+5AVK9bTvHkj&#10;tncHmHPQseO++Q04QSrcIiJSI7ggoFmP05nzkzHc+d7B7FN/A3cd/QoPHfsisx5/g9Gj23yjeDsH&#10;EyacQMuWjZMJOgG6xi0iIjVG3bqOcy5sw8xD9+KxZ+Zx+Ft/5Pg93qOdM5YuX8kdY09j8Qebeffd&#10;tbRurfu4RUREEtegQT1atWpCq1btca4D4fzXCR+5hxbvv0iL1XPo2v1cgoGngKudg8a1M2sREUmF&#10;KIpwhx9DMGIC7sz/gS1biH4/ma0jf0W0ZGHS4SVChVtERGo8V6cuwSk/Ixh1B65tZ/jwfcLfDCac&#10;cjPRJ6uTDi+vVLhFRCQ13C67Efz8MoLBt8B3WhLNfoXw+osJn3iYaNPGpMPLCxVuERFJHfedlgTX&#10;3oz7+eWwc0OiJx8mvO4SotmvFPz93CrcIiKSSi4ICNp2Ihg1GdflDPj8M8IpNxPeOpTow/eTDi9n&#10;VLhFRCTVXP0GBGdcQDBiIvzgWHhrAeHIXxH+fjLRF58nHV7WqXCLiEhBcHsVU3TpUILLhkOzYqIX&#10;nyEc0o9w+lNEW7cmHV7WqHCLiEhBca2PIhg2Hud/CVFI9PCdhDdcTvSv+UmHlhUq3CIiUnBcnToE&#10;J3ePbx874cewYhnh2OvYOnkM0eqVSYdXLSrcIiJSsFyTXQnOv5RgyK1w0KHwj1cJr+9P+PjviDZ+&#10;lXR4VaLCLSIiBc8dcBDB1TfiLrwSGjUh+rMRXncJ4ayXUnf7mAq3iIjUCs45gjYdCG74La6rh3Vr&#10;ie6+lfDmQUTL3k06vArLeeH23rfx3s8os2+s975vrs8tIiJSlqu/M0GPcwlGToIjj4N3FhOOuoLw&#10;gYlE69YmHd63yunqYN77gcB5wBeZx3sADwDfA97M5blFRER2xO25N0WXDCb613zCP9xF9PJzRLNn&#10;4n7SC3fiabg6NXMBzVz3uN8BepR63AgYBjyY4/OKiIhUiDv0BwTX347r1RccRI/cQzjyMqJFc5MO&#10;rVw5LdxmNg3YUurxB2b2BlB7VjwXEZEazxUVEXQ+nWDUFFyHLrByOeFtw9g6cRTRxx8lHd42auY4&#10;QBnFxcVJh1AlaY27opRfuim/dFN+OTszXD2KTWeez5opt7Bx/uuEi+bSuMc5NOn5C4KdG2TnLNXI&#10;L1+Fu1o97BUrVmQrjrwpLi5OZdwVpfzSTfmlm/LLg/qNiAYMw82eSfTYvax7dCrrnnsCd8YFuDYd&#10;cEHVB6wrkt+OCnu+bgcre5Ncum6aExGRWsc5R3DM8QQjJ+O69YINXxDdO47wpmuI3n87sbhy3uM2&#10;s6VA2zL7Rub6vCIiItng6tXD/aQ3UbuTiB69j2jOTMJfX4lr1xnX43zcLrvlNR5NwCIiIlIBbve9&#10;CPpdQ3DVaNivBdHMFwiH9iN8dhrRls15i0OFW0REpBLcwd8nGDoOd04/KKpD9Nh9hMMHEC2YnZfz&#10;q3CLiIhUkisqIjixK8HoO3AdT4PVHxGOH8nW8SOJVi7P6blTcTuYiIhITeQaNsb1voioQxfCP9wF&#10;C2YTLp6H69wNd3pPXJZuHytNPW4REZFqcvseQHDFDQQXD4JdmxI9Ny2+/j3zeaIwzOq5VLhFRESy&#10;wDmHO+pHBCMn4bqfA199STR1POGYgUTvZm95DhVuERGRLHI71SM4vSfBDZNxx7aHD94mvPFqwnvG&#10;Ea35pNrtq3CLiIjkgGu6B0GfqwiuvhGaf5fotRmEQy/mc5tKtLnqt4+pcIuIiOSQ+95hBENuxZ3X&#10;H+ruxNr7JxIO6080bxZRVPmJRFW4RUREcswFRQTtTyEYfQeNup8Nn64mnDSa8LbhRB/9u1JtqXCL&#10;iIjkiWvQiN36XkkwbDwcdiQsnks4YgDhI3cTbfiiQm2ocIuIiOSZ22d/gsuHE/QfAk33JHr+CcKh&#10;FxP+7VmicOsOj1XhFhERSYBzDndEG4IRk3A/Ox82bSR6cBLh6Ct3eJwKt4iISIJc3boEp55JMGoy&#10;7riOsOy9Hb5eU56KiIjUAG7X3XG//BVRt547fJ163CIiIjWI26t4h8+rcIuIiKSICreIiEiKqHCL&#10;iIikiAq3iIhIiqhwi4iIpIgKt4iISIqocIuIiKSICreIiEiKqHCLiIikiAq3iIhIiqhwi4iIpIgK&#10;t4iISIqocIuIiKSICreIiEiKqHCLiIikiAq3iIhIiqhwi4iIpIgKt4iISIrUyfUJvPdtgBvNrKP3&#10;/kBgKhACC82sf67PLyIiUkhy2uP23g8E7gLqZXaNBQabWQcg8N53z+X5RURECk2uh8rfAXqUeny0&#10;mb2c2X4GOCnH5xcRESkoOS3cZjYN2FJqlyu1vQ7YJZfnFxERKTQ5v8ZdRlhquzGwpiIHFRcX5yaa&#10;HEtr3BWl/NJN+aWb8ku36uSX78L9D+99ezP7G3AqML0Cx7hvf4mIiEjtkO/CfRVwl/e+LvAv4LE8&#10;n19ERCTVXBRFSccgIiIiFaQJWERERFJEhVtERCRFVLhFRERSJN9fTitoZaZ3PQJ4CliSeXqymT2a&#10;XHTVVya/PYlnxdsVKALON7P3Ew2wmsrk9zDQjPiuhhbAq2bWO8n4qqucn8/JwGZgiZldmGx01Vcm&#10;v6OI8/sKmGdmlyUbXdV57+sA9xL/HO4EjAYWUyDTR5eXn5k9mXluLPCmmd2ZXITVs533bxkwgXie&#10;k43Efz9XV7RN9bizpJzpXY8GbjWzTpl/aS/aZfO7GfidmZ0IXAccklBoWVE2PzM728w6Ec/89xlw&#10;eYLhVVs579/1wHAzaw/U996fllhwWVBOflOAAZnpldd679P8oetc4D+Z96oLMJHCmj66dH6nAhO9&#10;97t7758GuiUbWlaU9/7dBvTP/I2ZBlxbmQZVuLPnG9O7Aqd571/y3t/tvW+YUFzZUja/dsB+3vu/&#10;Ar2BF5MIKovK5ldiBDDBzD7OczzZVja/ucAe3ntHPBnS5kSiyp6y+e1nZrMy238Hjs9/SFljxB+O&#10;IR7d2gIcVUDTR5fOLyD+WWwEDAMeTCqoLCr7/m0GeprZgsy+OsCXlWlQhTtLypnedRYwMPOJ+D1g&#10;eBJxZUs5+bUAPjWzk4F/U8lPjDVNOfmRuRzQiXhIMtXKye9tYDywCNiLlH/wKie/d733J2S2uwGp&#10;/eBsZhvMbL33vjHwKDCEApo+urz8zGypmb1BAUzAtZ38Pgbw3rcF+gPjKtOmCnfuPG5mczPb04Aj&#10;kgwmBz4BnsxsP0k8wlBozgQeMrNCnOzgdqCdmR1G3KsZm3A82fYLYHBmRGgV8J+E46kW7/3+xDNN&#10;3m9mf6CK00fXVGXyeyTpeLKtvPy89z2B3wJdzeyTyrSnwp07z3rvf5jZ7gzMSTKYHHgZ6JrZbk/c&#10;cysEpT/hn0Q8DFmIPiHuqQGsIP6SYSE5DeidGRHaA/hrwvFUmfe+GfAscLWZ3Z/ZPdd73z6zfSrx&#10;72MqbSe/glFeft77c4l72iea2dLKtqlvlefOxcAE7/0mYCXQN+F4su0q4G7v/cXAWuLr3IWgdO+6&#10;JfFljkLUB3jEe78Z2JR5XEjeBqZ779cDM8zsL0kHVA2DiD9YXee9v574Z/Qy4r8vhTB9dHn5nWpm&#10;G9n29zGtyuZXBLQClgLTvPcR8JKZjahog5ryVEREJEU0VC4iIpIiKtwiIiIposItIiKSIircIiIi&#10;KaLCLSIikiIq3CIiIimi+7hF8sx7HxAvWnI28T2dOxGvJHe9mW2qQnv3AQvMrEKzn3nvOwO3EN8j&#10;u08mhg8zT48hnlinwu1VMtYOwEQz+34ljwuBPczs0zL7rwRam9nPsximSI2mwi2Sf3cQzy3dyczW&#10;ee93Bh4iXt3qglyf3MxeAI4E8N4PA3Y3swElz3vvu27v2CypyuQROzpGk1FIraLCLZJH3vsWxD3t&#10;vc1sPYCZfem9vwhomyniy4FjzeydzDHPEa/dOz3zfzviFYYeN7OhZdo/lHjJwKbEPenxZja1CqG2&#10;896fQbwm+ULg7EycXwF/Ag4HzgE2EM97vs35Mqvh3QccRDyv9hwzuyjTduPMeueHEC/D2cfMZnrv&#10;mwCTiOf1D4G/AIPMLCQzFW1mbeMJxNPRrgI+JuXzdItUlq5xi+TXUcCikqJdwsw+NrPHzexL4tXI&#10;+gB47w8knnr1KeAGoJ6ZHUzcY25Xar5qvPdFxKsPXWNmxwAnAgO998dWIc5i4pXRWgL7AT/L7N8J&#10;+JOZHQrMJ55qs7zz9QAamdlRwLGZ+L6baWNf4rXqjwTu5L8r500gXrf4+8APgR8QT61bWn/iDwOH&#10;AD8GmlchN5FUU+EWya+Qb/+9mwyclynEfYC7MiuUdQbuATCzzWbW0cz+Vuq4lsCBwL3e+7nAS0B9&#10;MsPilfS4mW3M9HYXEi/9WeKVCpzvFaCV934G8ZKvt5lZybzv75rZ7Mz2vFJtdwEmluRHfEnh1Mxz&#10;JcPhnYlXbNtqZhuA31chN5FU01C5SH69DhzqvW9Yutftvd8XmAKcYWZve+//CfyUeDi6ZJW5LZS6&#10;nuu93494qLpEEfBZppdb8pq9qNpQ8uZS2xHbrpr2xbedz8w2ee8PIu6FdwJe8N5fSrwq2fbaLvuB&#10;JgDqltlXNpYtiNQy6nGL5JGZrSDuJd7rvW8MUOra7urMikgQr9P7G+A1M1uV2fc8cIH33nnv6xEP&#10;U7cv1fxbwFfe+3My7e5P3FvO1Vrp2z2f974fMNXM/mpmg4iXNWydOc6V21r8mv6ZtuoRr6j3XJlj&#10;/gKc772v572vD/TMck4iNZ4Kt0j+XUK8FOPfvff/AF4lLnill9Z8CmhEPGxeYgRxb3U+8fruT5nZ&#10;4yVPZoaXuwMXeu/nExe5IWb2aiXjK/st7ai87W853wNA4L1f7L1/A2hM/CW28tovMQBo5r1fkMnx&#10;TeDXZY6ZQpz7QmAGhbvsqsh2aVlPkRrIe98WmFLZ+51FpPDpGrdIDeO9nwp0AM5LOBQRqYHU4xYR&#10;EUkRXeMWERFJERVuERGRFFHhFhERSREVbhERkRRR4RYREUkRFW4REZEU+X8qM2PTl1V7nwAAAABJ&#10;RU5ErkJggg==&#10;">
</div>
+
</div>
<div class="clear"></div>
+
<div class="clear"></div>
  
</p><p class="c0"><span><b>pSB1C3 absolute quantification run #2</b></span></p><p class="c0"><span>Lysate from 100,000 mid-log phase cells harboring K909006-pSB1C3 was compared against a 3-point standard of 10</span><span class="c1">5</span><span>, 10</span><span class="c1">6</span><span>, and 10</span><span class="c1">7</span><span> copies.  Due to the reduced amplification efficiency of the 10</span><span class="c1">8</span><span>-copy standard in run 1, cell numbers were reduced 10-fold in all subsequent experiments.</span></p><p class="c0 c2"><span></span></p><p class="c0"><span>Note: The K909006-pSB1C3 harboring cells used for this run were lysed in mid-log phase, which may account for the reduced PCN.</span></p><p class="c0 c2"><span></span></p><p class="c0">
+
</p><p class="c0"><span><b>pSB1C3 absolute quantification run #2</b><p>Lysate from 100,000 mid-log phase cells harboring K909006-pSB1C3 was compared against a 3-point standard of 105, 106, and 107 copies.  Due to the reduced amplification efficiency of the 108-copy standard in run 1, cell numbers were reduced 10-fold in all subsequent experiments. Linear regression indicates approximately 13.4 copies of the target sequence for every cell in the reaction, or around 12-13 plasmid copies per cell.</p><p>Note: The K909006-pSB1C3 harboring cells used for this run were lysed in mid-log phase, which may account for the reduced PCN.</p><p class="c0">
<div class="img-block">
+
<div class="img-block">
<!-- fig2 -->
+
<!-- fig2 -->
<img src="https://static.igem.org/mediawiki/2016/0/0a/T--genspace--pSB1C3_Absolute_Quantification_2.png" alt="">
+
<img src="https://static.igem.org/mediawiki/2016/0/0a/T--genspace--pSB1C3_Absolute_Quantification_2.png" alt="">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAe4AAAGMCAYAAAAcK0EHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz&#10;AAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmcTuX/x/HXdWbGvouYLEk5kZJKKkW0KJESp9Je9A2l&#10;tCd7FC0KlYr2hU6L+iqlhTYqUQrVUd+kBW3IMpgx5/r9cW5+Yxu3mbnnnjHv5+Mxj3Gf5Tqf+5ox&#10;n/u6znWuy1hrERERkeLBSXYAIiIiEj8lbhERkWJEiVtERKQYUeIWEREpRpS4RUREihElbhERkWJE&#10;iVtERKQYSU12ACKFyXXd1sAHwCNBEPTOsf0S4N4gCGok4JptgJlAhSAIMuI4/lCgehAEH+TjmpWA&#10;W4CuQF1gBfAGcGcQBCvyWm4e4tgHOCUIgkmx1zOBL4IguNl1XQM8CXQD/gSGAPcEQVCzAK67TR26&#10;rhsCHYMgmJbfsndyrdLAHcC5QGVgDnBdEATfFvS1REAtbil5LgAWA+fF/uDmlMjZiPak7NeBJnm9&#10;UCxZfg60AXoDLnBZ7Ptc13Ub5rXsPLgbODvH67OBobF/HwtcHNvWCphMPt73dravw1rAuwVU9vZG&#10;AV2I3ksLog9J77iuWyFB15MSTi1uKTFc1y1F1AK9DngUOAd4IalB7ZzJ5/kPAKuBNkEQZMe2/eq6&#10;7kfA28DjwIn5vEa8tnkvQRCszvGyKmCDIHgnx7ZNCbrunwVU7jZivQaXAFcGQfBhbNsVwCqgHfDf&#10;RFxXSjYlbilJOgKVgDeJuq4vZ7vE7brubcANsZfPADcGQRC6rptClBC7EnWHzgOuD4Lgi9h5DYF7&#10;iVq5IfBqbP+67cqvDywBmm7pSs3ZTR/rSq4PjHNdt2sQBO1c190XGAecBqyLxX9DEARrtn+DrutW&#10;Jep6PjtH0gYgCALruu5gYLbruo2DIPjOdd0lRN3TD+8sPtd1awL3A6fE3vevwIggCJ6MHT8T+BA4&#10;HDgV+BsYEgTBE7FrXRI7LjsIgpQtXeXAIqJuclzXzSZqhS8lx+0K13UPA+4DjgFWAuODIBgZ29cC&#10;uAtoSfR37GugbxAEc3ZRh1u7yl3XTQP6x2KrDcyN1eecXN7T0CAIHt++vol6LbsS/T5sEca+V9nJ&#10;8SL5pq5yKUkuAGYFQbCSKLGeGEtUW+xD9If6xNix3YGbY/uuAToBZxJ1wS4GXgJwXbcK8AlRa7EV&#10;Udfv8UQt253ZWbf5lm1dgN+IEkuX2LYpQDZRkuoIHEDUrbwzRxIlsk93tjMIgs+AjcBxuzh/+/ie&#10;JaqXtkBjoi7o8a7r5hwLcDMwjahepgAPx/bfC/jAVKKu6pwmAxfFrlUrduzWa7uuWx14n6gujgKu&#10;BG51XffSWBf0NOBL4FCiellH1IsCO6/DnB4k+tDWiyg5LwLejX1A2tV7emi79wxAEATZQRC8v11P&#10;wlVAKaKxFCIFTolbSgTXdSsDHYBXYpteI2oZXZrjsM1A9yAIFgZBMB0YTnSPGGB/ooT3axAEPwPX&#10;A5fEukovJPq/dHEQBN8FQfBxrNxuu7ifvMuu8CAIVhEl6bVBEKx2Xbct0BS4KFb2l0QJ7zTXdRvv&#10;pIh9Yt/X7uoaRK3XfXLZnzO+qcB/giBYFATBT8CdREmpUY5jZgZB8FisXgbE9jcLgmA9sAHYFATB&#10;X9u9z01E3fkEQfDXTgbtnQdkAj2DyHSiRLsOKEd0X/nWIAh+DoLgG2A8UT3tUIc5C439HlxONHhs&#10;ehAEQazcX4Grd/eecqmzLeW3Ae4BRgVB8MvujhfJCyVuKSnOJfrjOwUgCIJ/iLpDL8lxzO9BECzP&#10;8XoesF9shPZ4oALRveKPgf8A3wZBYIlaovODIMjMce4XRInnkHzG3QQoD6xyXXet67prgYDoQ8fB&#10;Ozn+n9j3OrmUWZlY0ozDeOAY13XHuq77NvAtUas4JccxP2z5RxAEWz4wpMVZ/q40Br4JgmBzjrIn&#10;BUHwcux+9USgj+u6E2P37p8mvr9njWLHfZajXAvMZtuf1R6/J9d1TyO6jTElCIKBccQikie6xy0l&#10;xQWx70tc192yzQDGdd2TYq+ztztnSyLICoIgcF23AdAeOB3oC1ztum5Lopb4zhi2TXCw827y3P4f&#10;pgI/AyezY0v9j50cP5eo5+Do2HnbcF33SKIPAl/sIp7UHMcaYDqQTtS1PYOoWznY7pxMdpTfAXaZ&#10;uyrDdd3aRI9cfQ+8FYutBvBcHOVu3EW5Dtv+rPboPbmu6xHdVphENIJfJGHU4pa9nuu69YjuOQ8m&#10;6u7c8nUkUdfr5bFD68TuV29xHLA0CIINruteCJwbBMEbQRD0IXq0qmas3O+Aw7d7vOxooiT43Xbh&#10;bEkIFXNs2747PWcy/Y4oca4LguCnWHd1NtFAuR2ed451E/vA4NggLFzXbeW67jeu63Yket54XqzL&#10;fUs828ey5frNiUZGnx4EwbAgCF4jGgkO8SfmvD5itxhoGhsUSOx9DHJd90XgfKIPU6cEQTA6CIL3&#10;iJ5Vj+e6PwJZ7HiP/1ii3oQ95rruqUQfGp4IguDSWAteJGHU4paS4EKie61jtx+J7bru00APohZo&#10;KjDJdd1biBLYbUSTmEA0Gn2Y67r/EP2B70iUvL4ElgGDgGdc1x0GVAceBt4NguD72KCnLYnuD6L7&#10;qTe4rnsr0QeIS7eLdx3QODYY6t3Y9V50XfdGoi7yB4m67X/exfu9jug2wEzXdYcC/wNmET2aZNk2&#10;aX0BXBzrBi9DlNi3JJ4VxO77u677PNGHlTGx/ds/A78r64BDXNetHwTB0jjPAXieaEKWh13XvQ84&#10;MPa+riX6sLGv67pnAAuJBs7dDtEjf7FbFlvrMOf99diHsHHAaNd11xONoL+WaBT6hD2Ij9j1SgNP&#10;EdXv0O0GuK0JgmDDnpYpsjtqcUtJ0B2YvLPHp4iSYCmiEeHfEiWyj4ju7d4bBMEEgNjjUg/Gtn9P&#10;NMq5axAE/4v9cT6V/5816yWiEcXn5LiOjZVjiRJ1Y6Ju52uJPiDkNIbow8bbsePPJLp3PSP2tQzo&#10;sKuWXez+/bGxGB4kSm4diR5vexWYHGt9Q5Twficahf4UUa9EGCtnWex99iRq+T8APAR8Q9RbsSs5&#10;43qK6JGrRbFHy+ISu698OtF9/Pmx6w4NguBZoh6FCUSPk30di69H7Lpb4tpahzuJ6Tbgxdj584h+&#10;FifGejO2P3Zn7ymn44F9gdZE9bgsx5e6zCUhjLWJ7dXxPK8lMNL3/bae5x1O9IcvC1js+36PhF5c&#10;RHYQ69rNCoJgZrJjEZE9l9AWt+d5NxF9Mt7SrTYIGOL7fmugjOd5ZyTy+iKyoyAI3lHSFim+Et1V&#10;/iPbzlP8FbCP53mGaEBMVoKvLyIisldJaOL2fX8K0eCWLX4AxhLd26uJZhYSERHZI4U9qnwM0Mr3&#10;/e89z+sNjGbb2Yp2Ro9WiIhISbTTxy4LO3H/w/9PxbiM3OdL3mrZsmW73Jeenp7rfsk/1XHhUD0n&#10;nuq4cKie8y89PX2X+wo7cfcEXvQ8L4vYPMSFfH0REZFiLeGJ2/f9pcRa1r7vzyJ67lFERETyQBOw&#10;iIiIFCNK3CIiIsWIEreIiEgxosQtIiJSjChxi4iIFCNa1lNERIqF+fPnM2zYMPbff38A1q9fT3p6&#10;OgMGDCAlZevS7VhrGT9+PEuWLCEzM5OyZcty7bXXUrt27d1eIzMzkxEjRrB69WrKlSvHrbfeSuXK&#10;lbc5ZtKkScyYMYPy5ctz7rnncuyxx7J27VpGjBjBhg0bqFSpEjfeeOPW87Kzs7njjjs444wzaNGi&#10;Rb7rQS1uEREpNpo3b87o0aMZPXo0jz76KCkpKcyaNWubY+bMmcM///zDPffcw5gxY+jUqRMPP/xw&#10;XOW//vrrHHDAAYwZM4ZTTjmFZ599dpv9S5YsYcaMGYwfP567776bJ598kszMTJ5//nkOO+wwxowZ&#10;w1lnncWECdHy7suWLeO6664jCIKCqQCUuEVEpJjKyspi5cqVVKxYcZvtVapUYfHixcycOZN///2X&#10;Vq1aMWTIEAA+/PBDevbsyU033cSQIUOYPn36NucuWLCAo48+GoCWLVsyb968bfYvXbqUww8/nNTU&#10;VEqVKkWdOnX48ccf+fnnn7eed+ihh7JgwQIANmzYwE033cThhx9eYO9bXeUiIrLHwpeexM6btdN9&#10;y1JSyM7O3uMyzZGtcLpdlusxX331Fddffz0rV67EcRw6depE8+bNtznGdV1uuOEGpk6dyrhx46hZ&#10;sya9e/fmkEMOYfz48UycOJHy5ctz66237lB+RkYG5cuXB6BcuXJkZGRss/+AAw7ghRdeYMOGDWRm&#10;ZrJo0SI6derEQQcdxOzZsznwwAP55JNP2LRpEwANGzbc43rYHbW4RUSk2NjSVT527FjS0tKoVavW&#10;Dsf89NNP1K1bl4EDB/Lqq6/So0cPhgwZwpo1a6hUqRIVKlTAGEOzZs12OLdcuXJs2LABiJJ4hQoV&#10;ttlfr149zjrrLG655RbGjRtH48aNqVy5Mt27d2f58uVcd911/Pnnn9SsWTMxFYBa3CIikgdOt8tg&#10;F63jwlhkpFKlSvTv359+/foxceJEqlWrtnXfvHnzWLp0KTfccAPGGOrXr0/ZsmWpWrUqGzduZPXq&#10;1VSpUoUgCDjuuG3XumratCmfffYZruvy+eefc+ihh26z/99//yUjI4OxY8eyfv16br75Zho0aMDn&#10;n39Op06daNKkCR999BFNmzZN2HtX4hYRkWKpfv36nHPOOYwbN47Bgwdv3d6lSxceeeQRevTosbV1&#10;ffvttwPQr18/+vfvT/ny5bd2Z+fUuXNn7rrrLvr27UtaWhoDBgwA4KWXXqJOnToce+yx/PLLL/Tq&#10;1Yu0tDSuuuoqjDHUrVuXu+66C4AaNWpw8803J+x9G2uL/HLXVst6JpfquHConhNPdVw4iks9T5gw&#10;gXr16tG+fftkh7KD2LKeO12PW/e4RUREihF1lYuISInUs2fPZIeQJ2pxi4iIFCNK3CIiIsWIEreI&#10;iEgxosQtIiIJYS1kZGSzeXORf3qpWFHiFhGRApWZmcWiRWsYMeJrzjzzHbp3n8n06cv4++/MAr/W&#10;lClT8l1Gnz59+OOPP/b4vF9++YV+/frl+/p7SqPKRUSkQE2Z8j0XXPAO2dn/39KeNWsFp5xSh7vv&#10;bknNmqUL7FrPPfccZ599doGVt6eM2emj1gmlxC0iIgXmt9820KPHjG2S9hbvvvsbs2c34Kyz6uax&#10;7N8YNWoUqamphGHIEUccwdq1axkzZgw9e/bknnvuYf369fzzzz907tyZM888k379+nHggQeyZMkS&#10;MjIyGDJkCDVr1mTixInMnTuXGjVqsGbNGgD++usvHnjgATIzM1m5ciWXX345rVq14vLLL6dOnTqk&#10;paXRp08fhg8fDkDVqlW3xjZx4kTmz59PGIa0bt2a8847L0/vMR5K3CIiUmAWL/6Xdeuydrl/3LgF&#10;nHxyOhUqpOxx2XPnzqVx48b85z//YcGCBVSuXJmpU6dy7bXX8sMPP3DSSSdx/PHH888//9CvXz/O&#10;PPNMABo3bkyfPn14/PHHef/99zniiCNYsGABjzzyCBkZGVx00UVA1PXteR7NmjVj0aJFPPXUU7Rq&#10;1YoNGzZwySWX0LBhQ8aOHctJJ53EGWecwcyZM5k6dSoAM2bM4P7776datWo7LBVa0JS4RUSkwKxd&#10;u+ukDfDHHxvYuDE7T4m7Q4cOTJo0iZtvvpkKFSpwxRVXbN1XtWpVXn75ZT766CPKlSvH5s2bt+47&#10;8MADgWgO8VWrVvHbb7/hui4QrQbWoEEDAKpXr86zzz7LtGnTALZZmrRu3aiX4Ndff6Vjx45AtCDJ&#10;lsTdv39/HnvsMVatWrV1Xe5E0eA0EREpMDVrls11/2GHVadChby1GWfNmsVhhx3GfffdR5s2bZg0&#10;aRJb1tvwfZ9DDjmE/v37c+KJJ5JzHY7t70PXr1+f77//HoANGzawdOlSAJ544gnat2/PbbfdRvPm&#10;zXdaxv7778/ChQsBtpaxefNmPvzwQwYOHMjo0aN5++23+fPPP/P0HuOhFreIiBSYRo0qUb9+BZYu&#10;XbfT/b17H0KZMnlrM7quy8iRI3n22Wex1m4dDX7nnXfSoUMHxo4dy8yZMylfvjypqalkZWXtdPDY&#10;gQceyNFHH81VV11F9erVt96rPvHEExk/fjwvvPAC++yzz9Z73znLuPDCCxkxYgQffPDB1rXAU1NT&#10;qVixIr1796ZMmTK0aNEioetxa3Uw2S3VceFQPSee6rhw/PxzJl27TmP58oyt24yBwYOP4oILGlKu&#10;3J53k5c0ua0Opha3iIgUqGOPrc8bb5zOd9+t5vvvV1G1ahkOP7w6BxxQnlKldIc2v5S4RUSkQBlj&#10;qFWrNLVq7UvbtvsmO5y9jj76iIiIFCNK3CIiIsVIsUjcduGXyQ5BRESkSCgWiTscM4Tsh0Zg/1qR&#10;7FBERCROxlpSMzJwckyGIvlXLBI3BzWB+Z8TDupDOOU57KaNyY5IRER2ITszk3KLFlFlxAiqn3km&#10;1bt3p8L06ZT6++98lZuZmcmbb765R+d88803LFmyJF/XLWoSPqrc87yWwEjf99t6njcJ2Jfo2bT9&#10;gU993+++uzKcm+7CfvEx9qUnsdN87KczMF0vxbQ4IbHBi4jIHts0ZQqVL7gAE5syNAVImzWLzFNO&#10;Yc3dd5OZx8lJVq5cybRp0zjjjDPiPuett96ibdu2W6c13RskNHF7nncTcBGwDsD3/fNj26sAM4Dr&#10;4inHGIM5ujW22dHYaS9j33kVO+Fe7AfTyOw7AMpUSNRbEBGRPVD6t98o26PH1qSdU6l336X07Nlk&#10;nnVWnsp+7rnnWLp0KU8//TRLlizZOrPZNddcQ4MGDRg1ahTLli0jMzOTLl26UL9+febMmcMPP/xA&#10;gwYNqFGjRr7eW1GR6Bb3j8DZwLPbbR8KjPN9f48mczWly2DOvhDb6iTCl56A+Z/zx7UXYlqfhunc&#10;HVOhUkHFLSIieZC2eDFm3c6nOwUoO24cG04+mc0V9rzBdeGFF7JkyRIyMzM54ogjOPPMM/n9998Z&#10;NWoUo0aNYsGCBTz00EMAzJs3j0aNGnH00UfTrl27vSZpQ4ITt+/7UzzPq59zm+d5NYB2xNna3hlT&#10;szYpfW7HLpyH88pTbP5gGvaLjzFnXYBp3R7jaDo9EZFkMGvX5rrf+eMPnI0bIQ+Je4uffvqJL7/8&#10;kg8++ABrLWvXrqVs2bL06dOH++67j4yMDE4++eQ8l1/UJWPmtK7AC77vxz1JemzO1p3twLY9jbVT&#10;X2TNCxOwzz9C6uwZVLnqRso0PaKAwhXI5WcgBUr1nHiq48TK2G+/XPdnN2tG5Xr1SKtSZY/LNsaQ&#10;mppKkyZNaNq0KWeccQYrV67k5ZdfJi0tjeXLlzNx4kQyMzM58cQTufTSSylfvjxVqlTZq37uhZW4&#10;c06UfjJwx56cvLtFRtYd0w7TuDm8+gxZs9/nr1uuxLQ4AdP1Mky1ffIYsmyhhRkKh+o58VTHiVeq&#10;QQNK169PSmypzO1t6NWLdRkZkJGx0/25yczMZMOGDfz5559MmTKFZ555hoyMDC699FKysrJYunQp&#10;Xbp0ISUlhW7durFixQrq16/PqFGjKF26NPXq1cvv2ys0uX3QKKzEnbN13Qj4qaAvYCpXxVx2LbbN&#10;aYSTHotGoX89B9OhG+bUszBppQr6kiIisp3M6tXZ9MILlOnaFWf58q3brTFkDB7MhiPy3htaqlQp&#10;HnvssV3u79ev3w7bOnXqRKdOnfJ8zaJor1zW04Yh9tMZ2FeehrX/Qo1aON4V0Ozona7NKrlTK6Vw&#10;qJ4TT3VcOGrXrs0/X31Fqe++I+X777FVq5J1+OFsOuAAwlJqRMWjxC3raRwH0+pkbPNjsVMnY2e+&#10;QfjQCDikOc65PTG16yQ7RBGRvZYxhsxatcisVQvatk12OHud4jFzWh6ZcuVxzr0CZ9AYaNwMFn1F&#10;OPQawpeewG7Y8/srIiIiybZXJ+4tTHo9nH7DcHr3hyrVse+8RjjgKsJZ72PDMNnhiYiIxK1EJG6I&#10;zb7W/BicYQ9hOl8AGzOwT40hHHkzdskPyQ5PREQkLiUmcW9hSpXG6XguzrDxmKOOhyWLCe+8gfCp&#10;sdg1q5IdnoiISK5KXOLewlSvgfOfm3FuHAH71cfOeo9wQC/Cd1/Hagk6EREpokps4t7CuIfiDHwA&#10;0/0/YBys/zjhsGux336V7NBERER2UOITN4BJScFpewbO8EcwbU6DFb8R3j+Y7IfuxP61ItnhiYiI&#10;bKXEnYOpWAnnwt44A0bDgU1g/meEg/oQvvYcdtPGZIcnIiKixL0zpl5DnJvvwvS4ASpUxL7pEw7q&#10;TfjFJxSDmeZERGQvpsS9C8YYnJZtcO4Yjzm9K6xZjX3sbsJ7b8f+tiTZ4YmISAmlxL0bpkxZnC4X&#10;4wx9EJodDYsXEg7rR/jCI9j1ua87KyIiUtCUuONkaqaTcvUAnL6DoWZt7Mxp0exrH7yFDbOTHZ6I&#10;iJQQStx7yBx6JM6QsZiul0HWZuzz4wmHX4/94dtkhyYiIiWAEncemNQ0nPZn4wwfjzm2Lfy6hPDu&#10;Wwkn3Idd9U+ywxMRkb2YEnc+mCrVcC7vh3Pr3VD/QOycDwkH9iKc9hI2KyvZ4YmIyF5IibsAmIYH&#10;4/S/F3Px1VCqNHbKs4SD+2C/nqPHx0REpEApcRcQ4zg4J5wadZ+ffCb88yfhg8MJxw7Frvgt2eGJ&#10;iMheQom7gJlyFXDO7YEzeCw0bgYLvyQccg3hS09iN2QkOzwRESnmlLgTxKTXw+k3DKfXrVClOvad&#10;KdH979kzsGGY7PBERKSYUuJOIGMM5ojjcIY9hDmzO2Ssxz75AOGoW7A//5Ds8EREpBhS4i4EplRp&#10;nE7n4dzxMObIVvBTQHjnjYRPj8OuWZ3s8EREpBhR4i5EpnpNnKtuwblhOKTXw37yLuGAXoTvvY7d&#10;vDnZ4YmISDGgxJ0E5uDDcAY+gDn/SjBgX3yccNi12G/nJzs0EREp4pS4k8SkpOC064gz/BFM69Ng&#10;xW+E9w8ie/xd2L//SHZ4IiJSRClxJ5mpWBnnot44t4+GhgfDl58SDupD+PoL2E2bkh2eiIgUMUrc&#10;RYSp3xDnllGYK66HchWwb0wmHNQLO/cTzb4mIiJbKXEXIcYYnGNOxBn+MOb0c+Df1YSP3k143wDs&#10;bz8nOzwRESkClLgTwBiTv/PLlMPpcgnO0AfhsBYQLCC84zrCSY9h16/LV0z5jU1ERJIrNdkB7C2y&#10;siyLF69lxozfWbhwJU2bVqNdu/1o1KgiaWl5S5Zm33RSrhmIXTCXcPJE7Iw3sHM+xJx9Eeb4UzBO&#10;SlwxzZ//N+XKpbF48Wp+/HENhx2W/9hERCQ5TDG4f2qXLVu2y53p6enktr8wZGVZpk79lb59PyFn&#10;dRoDY8ceT6dOdfOdIG1WFvb9/2Lf8GHTBqh3AM75V2IObJJrTI8++i0dO9Zn1Kiv8hxbUajjkkD1&#10;nHiq48Khes6/9PR0gJ3+cVZXeQFYvHjtDkkbwFro2/cTFi9em+9rmLQ0nNPOie5/H9MWfvmJcNSt&#10;hBPvw676Z5cxdevWcIekXdCxiYhI4VHiLgAzZvy+Q2LcwlqYOfP3AruWqVId54p+OLeMgnoNsZ9/&#10;GC1e8tYr2KysbWKqXbscv/yyrtBiExGRxEv4PW7P81oCI33fb+t5Xg1gAlAFSAEu9n1/SaJjSCRj&#10;DAsXrsz1mIULV2GMKdDHusyBjXFuvxc7633sq89gX30a+8k70ZKizY5m4cKV1KoVJe7Cjk1ERBIn&#10;oS1uz/NuIkrUpWOb7gae833/RGAgcHAir18YrLU0bVot12OaNq2akMRonBScE06NZl87qRP8/Qfh&#10;uDvYPGYorQ7KZsWKDOrVq5CU2EREJDES3VX+I3B2jtetgDqe570LdAc+SPD1C0W7dvuxq6esjIG2&#10;bfdL6PVN+Qo45/XEGTQGDj4MFsyl+w/3c0ml2RywX2pSYxMRkYKV0MTt+/4UIOeyV/sDK33fPwX4&#10;Fbg1kdcvLI0aVWTs2ON3SJDGwLhxJ9CoUcVCicPsVx/n+jtwrroVqlSj1wHf0+GzETx+pcWYbVvV&#10;hR2biIgUjMJ+jvsfYGrs31OB4YV8/YRISzN06lQX1+3IzJm/s3DhKpo2rUrbtoX/rLQxBo48jpSm&#10;R7L5rVep+vbLnPzri3x1fgPerNiBT3+vUCDPmIuISHIUduL+GOgAPA+0BhbFc1LsebY87y8s9evD&#10;SSc1IgxDHMfBcZI8aL/3DWzu2p1VE++n2qwZXPTvw1x5yplUvrg3aVWr71FRRaWO93aq58RTHRcO&#10;1XPiFHbivhGY6HleL+Bfovvcu1XUJ2Ap8i69DqdlW8LJE9jwzuts+Pg9TOfumDanY1J3/yugOi4c&#10;qufEUx0XDtVz/uX2wUczp5UgdvNm7IdvYV9/ATash/R6OOf1xDRulut5quPCoXpOPNVx4VA9559m&#10;ThMATGoqzkmdcEY8gjnhVFj+K+HogWSPH4n9+49khyciInFQ4i6BTMXKOBdfjXP7fdDwYPhyNuGg&#10;PoT/nYTN3JTs8EREJBdK3CWYqX8gzi2jMFf0g3IVsFMnEQ7qg503W5OyiIgUUUrcJZwxBueYttHi&#10;Je27wOqVhI+MJBw9EPv7L8kOT0REtqPELQCYMuVwul6KM2QcND0Svv+GcFhfwskTCNeuSXZ4IiIS&#10;o8Qt2zC19iPl2sE41wyEffbFvj+V5Vd2IfxoOjbMTnZ4IiIlnhK37JQ5rAXOkAcxXS7BZm7CPvsQ&#10;4Z03YX/8LtmhiYiUaErcsksmLQ3n9HOo/dirmGNOhKU/Eo66hfDx+7Gr/0l2eCIiJZISt+xWSvUa&#10;OFdcj3PLSKh3APazmYQDehO+/Qo2KyvZ4YmIlChK3BI3c2ATnNvvw1zUG9JSsa88TTjkGuyCuckO&#10;TUSkxFDilj1inBSc1qfhDH8U064j/L2CcOwwsscOw/6pKQ5FRBKtsBcZkb2EKV8Bc/6V2BNOJZw8&#10;ARbMJfzeBNdYAAAgAElEQVRuPuaUzpgOHqZM2WSHKCKyV1KLW/LF1Nkf54bhOFfdApWqYt96hXBg&#10;L8LPPtDsayIiCaDELflmjMEc2Qpn2MOYjufBurXYx0cT3n0rdun/kh2eiMheRYlbCowpXRqnc3ec&#10;YQ/BEcfCj98Rjrie8NmHsGv/TXZ4IiJ7BSVuKXCmRi1Set2G028Y1KqD/Wg64YCrCN9/A5ut2ddE&#10;RPJDiVsSxjQ5HGfQGMy5PcCCnfwY4R3XYb//JtmhiYgUW0rcklAmNRXn5DNxho/HnHAqLPuF8L4B&#10;hI+Mwv7zV7LDExEpdpS4pVCYSlVwLr4a57Z74QAXO28W4aBehFMnYzM3JTs8EZFiQ4lbCpVpcBDO&#10;LaMwl10HZctj//sC4aA+2C9n6/ExEZE4KHFLoTOOg3NcO5w7xmPanw2rVxKOH0l4/yDssl+SHZ6I&#10;SJGmxC1JY8qWw+l6Gc6QsdD0CPjua8KhfQlfnIjNWJfs8EREiiQlbkk6U6sOTt/BOFcPhOo1se/9&#10;l3BAL8KP38GGYbLDExEpUpS4pUgwxmCatcAZ+hDm7Itg00bsMw8S3nkj9n/fJzs8EZEiQ4lbihST&#10;lobToVt0//voNrD0R8KRNxM+cT929cpkhyciknRK3FIkmWr74PS8AefmkVC3AfbTmdHiJdNfxW7O&#10;SnZ4IiJJo8QtRZo5qAnOgNGYC3tDair25acIh/TFLpyX7NBERJJCiVuKPOOk4LQ5DWf4I5i2HeDP&#10;5YRjhpL94HDsn8uSHZ6ISKFKTXYAIvEy5Stiul+Fbd2ecNIE+HoO4aIvMaechenQDVOmbLJDFBFJ&#10;OLW4pdgxdRrg3DgCc+XNULEK9q2Xo/vfn3+o2ddEZK+nxC3FkjEGp8XxOHc8jOl4Lqxbi514H+Hd&#10;t2F/+SnZ4YmIJIwStxRrpnQZnM4X4Ax7CJofAz9+Szj8esLnHsauXZPs8ERECtxuE7fneUcURiAi&#10;+WFq1CKld3+cfkOh1n7YD98mHHAV4cw3sdnZyQ5PRKTAxNPifj7hUYgUENOkOc6gMRjvCrAh9oVH&#10;Ce+4DhssSHZoIiIFIp5R5d94ntcd+ATYuvKD7/txTWPleV5LYKTv+209zzsceANYHNs93vf9l/Yw&#10;ZpFcmdRUzCmdsS1bY199FjvrPcJ7b8ccdTym62WY6jWSHaKISJ7Fk7g7A92222aBlN2d6HneTcBF&#10;/H/CPxK4z/f9+/ckSJG8MJWqYi7ti21zGuGkx7BzP8F+MwdzeldM+y6YtFLJDlFEZI/tNnH7vl8m&#10;H+X/CJwNPBt7fSTQyPO8s4AfgGt931+fj/JFdss0aIRz693Yz2ZiX3ka+/oL2Fnv43hXwOEtMcYk&#10;O0QRkbjtNnF7nucA1wNNgWuAq4G7fd/f7Ygf3/eneJ5XP8emz4EJvu9/5Xlef2AIcFNeAhfZE8Zx&#10;MMedhD38GOybL2Lfn0r48J3Q5HCc83piatdNdogiInGJZ3DaPcBhQMvY8acBee3qfs33/a9i/54C&#10;HJ7HckTyxJQrj9PtcpzB46BJc/h2PuHQvoQvPo7NUOePiBR98dzjPgk4Apjn+/6/nuedCszP4/Wm&#10;e553te/7c2PlxrVSRHp6er72S/7tdXWcno49ogUbP/+IVRNGk/3e65i5H1Ppkj6UP7kTxknOFAd7&#10;XT0XQarjwqF6Tpx4EneW7/uh53kA+L6/yfO8zXm8Xi9gnOd5mcAK4Mp4Tlq2bNcLSaSnp+e6X/Jv&#10;r67jegdhB43BvPMa4bSXWDXmDla9Phnn/CsxB7iFGspeXc9FhOq4cKie8y+3Dz5md3M7e573JDAX&#10;+A/R6PLrgXK+719UgDHmxipxJ1dJqWO78m/sK09h53wEgDnuJEyXizGVqxbK9UtKPSeT6rhwqJ7z&#10;L5a4dzpyNp7+wGuJusr3BWYBFYDrCio4kaLCVNsHp+eNODfdCXUaYGe/H82+9s4U7OasZIcnIgLE&#10;9zjYGuCKQohFpEgwjZriDByN/Wg69rXnsS89if34HZxze2KaagZgEUmueB4HqwmMAU4BsoBpwA2+&#10;769OcGwiSWOcFMyJHbBHHR899/3h24RjhkCzo3HO7YGpUSvZIYpICRVPV/kE4CfgaOAEYBXwaCKD&#10;EikqTIVKOBdchTPwfmh0CHw9h3BQH8Ipz2E3bUx2eCJSAsUzqnx/3/c753h9o+d5WrFBShRTtwHO&#10;jXdG06a+9CR2mo+d/T6m22WYFido9jURKTTxtLiXeZ7XYMsLz/PqAMsTF5JI0WSMwWlxAs4dD2M6&#10;eLDuX+yEewnvuQ3765JkhyciJcQuW9ye500lWkykBjDf87z3gGygLfBN4YQnUvSY0mUwZ1+IbXUS&#10;4UtPwPzPCe/oh2nTHtP5AkyFSskOUUT2Yrl1lb+8i+1vJiIQkeLG1KxNSp/bsQu/JHxxAvaDt7Bf&#10;fII56wJM6/YYZ7cL6ImI7LFdJm7f95/O+drzvHKJD0ek+DFNj8A5eCx2xpvYqZOwzz+C/XA6zvk9&#10;MY2aJjs8EdnLxPM4WD9gBFA6tskQ53rcIiWFSU3DnHoWtmUb7JRnsLPeJ7ynfzRwreulmGo1kh2i&#10;iOwl4hmcdj1wDFAp9lUx9l1EtmMqV8W59Fqc2+6B/Q/CfvEx4cDehG/62KzMZIcnInuBeB4H+8H3&#10;fQ1GE9kD5gAX57Z7sJ/OwL7yNPa157CfvItz7hXQrKUeHxORPIsncT/oed6LwDtEM6cB4Pv+MwmL&#10;SmQvYBwH0+pkbPNjsW9Mxs54g/ChO+GQ5tH0qbXrJDtEESmG4kncfYgWGMk5OM0CStwicTDlymO8&#10;K7AnnEo4eQIs+opw6DWYkzphOp6HKatxnyISv3gSdz3f9w9KeCQiezlTuy7OdUPh688JX3wc+85r&#10;2M8+wHS5BHNs22SHJyLFRDyD0372PG/XK3qLSNyMMZjDj8EZ9hCm8wWwMQP71BjCkTezKViY7PBE&#10;pBiIp8W9AVjoed4XwKYtG33fPzNhUYns5UxaKUzHc7HHtcO+/BT2i4/58/pLMa1OwnS5GFOparJD&#10;FJEiKp7E/UrsS0QKmKlWA3PlTdg2p5Py8hNkzXof++WnmE7nY9qegUmN57+oiJQkxlqb7Bh2xy5b&#10;tmyXO9PT08ltv+Sf6rhw1N63Jr9Pfgr72nOQsQ5q18U5rwemSfNkh7bX0O9y4VA95196ejpEE57t&#10;IJ6Z09YSjSLfhu/7moRFpACZlFScth2wLY6Pnvv+aDrh/YPh8GNwvMsxNWolO0QRKQLi6YfLOdly&#10;KaAL0SphIpIApkIlzIW9sa3bE06aAPM/I1w4D9P+bMzpXTGlyyQ7RBFJot0mbt/3l263aZTneZ8D&#10;9yYmJBEBMPUa4tx8F3bOR9EAtjd97OwZmG6XYY46XrOviZRQ8TwOtg3P8w4mmpBFRBLMGIPTsg3O&#10;HQ9jOnSDtauxj91DeO/t2N+WJDs8EUmCPb3HbYi6y29OZFAisi1Tpizm7IuwrU4m9B+Hr+cQDuuH&#10;OfE0TOcLMOUrJjtEESkke3qP2wKrfd9fk6B4RCQXpmZtUq4egF04j3DyROzMadg5H2POuhDT+lSM&#10;o9V2RfZ2u+wq9zyvnud59YiS9ZYvgCqx7SKSJKbpkThDxmK6XgbZm7HPjyccfj128aJkhyYiCZZb&#10;i3sRUbLOOQLGAmWJEr4+2oskkUlNw7Q/G9uyDfbVZ7CfziC85zbM0a0xXS/DVK2e7BBFJAF2mbh9&#10;39/mppnneQboD9wY+xKRIsBUqYa5/Dpsm9MIJz0WjUL/eg6mQzfMKZ0xaaWSHaKIFKC4RpV7nrcf&#10;MAM4G2jp+/7jCY1KRPaYaXgwTv97MZdcA6VKY6c8Szj4auzXc9h+hkQ9SiZSfMUzqrwL8BjwFHCb&#10;7/tZiQ5KRPLGOA7m+FOwRxyLnfoidsZUwgeHQ9MjSDnnUsr+u55SM2aQunAhm5s2JbN9ezY1bEiY&#10;ojtfIsXFLhO353llgTHAGcB5vu+/V2hRiUi+mHIVMOdegT3hFMLJE2Dhl2Qv+gr+t4KyPy4jPLgJ&#10;2S1aUPa55yi/fDmbDzuMzHbt2NCoETYtLdnhi0gucmtxfwnUJ0reh3med1jOnb7vj05kYCKSfya9&#10;Hk6/YZT670tk+Y+z7oB9yahfk3L1m1J5yBCcWBd6qWnTKDtqFGkjRpB5zDFsPOAAJXCRIiq3e9yf&#10;Ay8CtYBDt/tqmst5IlKEGGMo98sf1PpoEZUW/06Ylsq63xbx1zGN2FS53P8fZy3lbr+d0h99RIWp&#10;UzFZuismUhTlNqr80kKMQ0QSxBhD6sKFOKGlYoZD6j4uG+Z/wob0avx53MGU/+0fKge/k5K5GWMt&#10;zq+/UnrCBDa7LhsOOSTZ4YvIdvZ4rvI95XleS8/zZm63rbvnebMTfW0RAWstm5tGnWRhrVqU+n0F&#10;+8xfQo3PAtLWbmB93X1Y3uYQ1u5fE2vA+fVXbM2alJo5czcli0gyJDRxe553EzABKJ1jW3Pg8kRe&#10;V0S2ldmuHdYYnBUryK4XTXxYZuU69p31HVUW/QLA6iZ1WXF8EzbWrILzxx+kLlyox8ZEiqBEt7h/&#10;JHr2GwDP86oDw4FrE3xdEclhY6NGrBs7FrN8OWG9ethYQjYWKi79i9ofLKT8L3+xuUIZ/l35P1bW&#10;KsOmRg13eP5bRJJvt4nb87wvPc/r4Xleud0duz3f96cAm2PlOMBE4HpgPdtOpSoiCWTT0ljXqROr&#10;p08nu1w5NgwZsjV5A6RkZVN10a9UaXQsaRtDNtSqyr+LPyV8/QXspk1JjFxEtmd294na87zjgP8A&#10;pwKvAON93497JQPP8+oDk4C+wJPAX0TznTcGnvB9//rdFKGP/CIFKAxDstavJ2vuXFLeeIOUhQsJ&#10;69YlrFuXUi+/jLNoEf/2v56MnxcSrvqblBr7UuWKfpQ9/iR1nYsUrp3+h9tt4t7C87wqQHfgBmAZ&#10;MNb3/ZfiOK8+MNn3/WO32zbJ9/3j4ri0XbZs2S53pqenk9t+yT/VceFIRj2bzZsp8+uvpH34IWmf&#10;fRbNpta2LRsbNSLM3oyd9hL23ddg82ZwD8U5ryemzv6FGmNB0u9y4VA95196ejrsInHHsx73lqR9&#10;EXAF8C/gAxd7ntfJ9/2L4yhCrWaRIsimprKhQQM2NGiAueyybe5pm7Q0TJeLscefTPji4/DNF4TD&#10;rsOceDqmc3dM+Yq5lCwiiRJPV/nzQAfgDeBh3/c/jW1PBf70fb9agmNUizvJVMeFo6jXs10wl3Dy&#10;RPhzGVSoiDn7Iszxp2Ccnc9zbozJdXDbzvbv7pz8Kup1vLdQPedfflvci4DrfN//K+dG3/c3e57X&#10;Kv/hiUhxYA49CqdxM+z7U6MFTJ59GPvh2zjnX4k5sAkAWVmWxYvXMmPG7yxcuJKmTavRrt1+NGpU&#10;kbQ0s9P9p55ah6yskJkzl+30HBHZVlz3uD3P6wC0B7KBqb7vF+bMDGpxJ5nquHAUp3q2q1diX30a&#10;+2n0p8C0bEN250uY+nEGfft+Qs4/K8bA2LHHc/rpdXjrrd+22d+0aTU6dqzPqFFf7fScTp3qFmjy&#10;Lk51XJypnvMvtxZ3PI+DDQbuI7q3nQE86nle34IMUESKF1OlGs7l/XBuvRvqH4j9/EMY3IvvHniM&#10;NJO9zbHWQt++n7Bgweodknq3bg13SNo5z1m8eG0hvBuR4iWeCVguAo7xfX+Q7/sDgJZAr8SGJSLF&#10;gWl4ME7/ezAXX82mMJVb3W9494S3aFdj29aWtTBz5jJq1/7/6SDS08vxyy/rdkja257zeyLDFymW&#10;4knc/wA5P/auBtYlJhwRKW6Mk0JK6/YMCHvw+JJG1C27nqdafMSTR31Ig/Jrth63ePFq9t33/xN3&#10;rVpR4s7NwoWr9Oy4yHbiGZw2F3jd87xHiWZBuxD4xfO8LgC+77+awPhEpBiw1tLw0HSGvnkEk35t&#10;yNAm8zip5nJO2OcPHl/SiLE/HkKjRlX45pu/t56zYkUGzZvXyLXcpk2ratpVke3E0+JuAlQgmnjl&#10;FmA/oBpwDXB14kITkeKkXbv9MAYWr6vM+XPacuW8VvyxsQy9Gn7Ph23e5Jw6S1ixfP3W45cty6Be&#10;vQrsqkFtDLRtu18hRS9SfOzJzGmpgPF9PyuxIe1Ao8qTTHVcOIp7PWdlWaZO/XWbAWilnc1c1fB7&#10;rnMDUsIsVlZpwEVvHsSCf6PpH3IbVT5u3Al07FhHo8qLIdVz/uXrOW7P82oCTwPtgFTP8z4ELvR9&#10;Xz8VEdkqLc3QqVNdXLcjM2f+zsKFq2jatCpt256Fqb4BXnuSavNm80arn/mu2lE8vfoY9j+0Dqec&#10;Uoe2bdP54INlOc7Rc9wiuxLPPe4Hgc+A84EUosVCxgOdExiXiBRDaWmGQw6pxCGHVNpuFrRKcNWt&#10;2O++Jpw8gSbLvmBU2W8xjbtjGh6ESU2ladPKCZ85TWRvEE/ibuT7vpfj9WDP8+JeHUxESqadJWDT&#10;uBnOoDHYD97C/vd57OQJ2I+mR4uXNG6mpC0Sh3gGp6V5nldmy4vYutz63yUieWJSUnBO6ogz/BFM&#10;6/aw/FfC0QPJHj8S+/cfyQ5PpMiLp8U9GXjP87wnY68vA15OXEgiUhKYipUxF/XBtm5POOkx+HI2&#10;4YK5mNO6YNqfgyldOtkhihRJu21x+75/B/A4cCpwGvAUMDSxYYlISWHqH4hzyyjMFf2gXAXs1MmE&#10;g3pj581W17nITuTa4vY8Lw0o7fv+k8CTnucdCnzv+77+N4lIgTHGYI5piz28JfbNl7Dvvk74yEg4&#10;+LDo/vd+9ZMdokiRscsWt+d5dYiW9OyYY/MAYIHneemJDkxESh5TphzOOZfgDH0QDj0Kvv+GcNi1&#10;hJMnYNdrpmURyL2r/B7gCd/3J2/Z4Pv+ucBzwN2JDkxESi6zbzopfQfhXDMQ9tkX+/5UwgFXEX40&#10;HRtm774Akb1Ybom7qe/7I3ey/U7giATFIyKylTmsBc6QBzHnXAJZWdhnHyIccSP2x++SHZpI0uSW&#10;uDN3ttH3/RDYmJhwRES2ZdLScE47B2f4w5hjToRf/kc46hbCx0djV/+T7PBECl1uiXuN53kNtt/o&#10;eV5DolXCREQKjalSHeeK63FuGQn1GmI/+4BwQG/Ct1/BZhX2EgoiyZPbqPL7gKme5/UFZhMl+WOA&#10;MUTd5SIihc4c2ATn9nuxn7yHnfIs9pWnsR+/i3NeD8yhRyU7PJGE22WL2/f9N4gS9ERgPbAWeAi4&#10;0/f9SYUTnojIjoyTgtO6fTT72kmd4O8VhGOHkT12GPYPrX8ke7dcn+P2ff8F4AXP86oBoe/7qwsn&#10;LBGR3TPlK2DO64k94dRo9rUFcwm/nY85pTPmDA9TpmyyQxQpcPFMeYrv+ysTHYiISF6Z/erj3DA8&#10;mjbVfwL79ivYz2ZizrkU07INxmh5UNl7xLPIiIhIkWeMwRzZCmfYw5hO58H6ddjHRxOOugW79H/J&#10;Dk+kwChxi8hexZQujXNmd5xhD8ERx8H/vicccT3hsw+R/e+qZIcnkm+77Sr3PK/edpsskOH7vh6g&#10;FJEiy+yzLym9bsV+9zXhpMewH01n+bzZ0Ol8zImnY1JSkh2iSJ7E0+KeBSwBvgHmAz8DyzzP+93z&#10;vOMSGJuISL6Zxs1wBo3BnNsDsNjJjxHecR32+2+SHZpInsSTuN8DLvN9v4rv+9UAj2hpz47A/QmM&#10;TUSkQJjUVJyTz6T2Y69iTjgVlv1CeN8AwkdGYf/5M9nhieyReBJ3M9/3n9nywvf9V4Ajfd//CiiV&#10;sMhERApYSpVqOBdfjdP/XjjAxc6bRTioN+HUydjMTckOTyQu8STuVM/zmm55Eft3iud5ZYC0hEUm&#10;IpIgZv+DcG4Zhbm8H5Qtj/3vC4SD+mC/nI21NtnhieQqnue4bwU+8DxvEVGiPwjoDgwFpiQwNhGR&#10;hDGOgzm2LbZ5S+wbPva9/xKOHwmNm+Gc2xOz3/bjckWKht22uH3fnwY0IrqfPRJo7Pv+DGC47/sD&#10;ExyfiEhCmTLlcLpeijNkHDQ9Er77mnBYX8IXJ2Iz1iU7PJEdxPM4mAP0ADrEjn/H87w7fd9fm+jg&#10;REQKi6m1H07fQfDNXMIXJ2Df+y/28w8xZ1+EaXUSxtHjY1I0xNNVfhfQDHiAqIV+JXAP0C+eC3ie&#10;1xIY6ft+W8/zmgCPxnb9APSIre8tIpJ0xhho1gKnyeHY917Hvuljn3kQ++HbOOdfiWl4cLJDFIlr&#10;cNppQCff91/zff9VoDNwejyFe553EzABKB3bNAK41ff9EwADdNrzkEVEEsukpeGc3hXnjvGYlm1g&#10;6Y+EI28mfOJ+7Got3SDJFU/idnzf37pKve/7m4B4V63/ETg7x+suvu/P8jyvFFAL+DfuSEVECpmp&#10;Wh2nxw04N4+Eug2wn84kHNCLcPqr2M3x/hkUKVjxdJXP9zzvfuDB2Os+RLOo7Zbv+1M8z6uf47WN&#10;TaH6HrAa+HoP4xURKXTmoCY4A0ZjP34X+9qz2Jefwn78Ls65PTCHHpns8KSEiSdx9wHGArOJuren&#10;A9fk9YK+7/8CNPI87wqikeqX7u6c9PT0fO2X/FMdFw7Vc+Llq47Pv5zsjuew5rlHWTftZcKxQylz&#10;9AlU6Xk9ael1Cy7IvYB+lxNnt4nb9/01bJdcPc87BNjjGz2e570O3OD7/o/AWiA7nvOWLVu2y33p&#10;6em57pf8Ux0XDtVz4hVYHXe+EOfIVoSTJ7Jxzses+PJTzClnYTp0w5Qpm//yizn9Ludfbh984mlx&#10;78ynQKU8nDcSeMrzvE1ABtFjZiIixY6p0wDnhuEwbxbhS09g33oZ++kMTNfLMEe3jkaoiyRAXhN3&#10;3L+Rvu8vBY6L/ftT4Pg8XlNEpEgxxsBRx+Mc2gL79ivR18T7sB+8hXN+T0y9hskOUfZC8Ywq3xlN&#10;5isiEmNKl8bp3B1n2EPQ/Bj48VvC4dcTPvswdu2aZIcne5m8Jm4REdmOqVGLlN79cfoNhVp1sB+9&#10;TTjgP4Qz3sBmxzWkR2S3dtlV7nneWnbesjZAuYRFJCJSzJkmzXEGjcF+8Cb2v5Owkx7DfjQ9mn3N&#10;PTTZ4Ukxl9s97qa57BMRkVyY1FTMyZ2xR7fBTnkWO+s9wntvxxx1fDSArXqNZIcoxdQuE3dsUJmI&#10;iOSDqVQFc8k12NanEU56FDv3E+w3czCnd8WcejamVOndFyKSg+5xi4gUAtPgIJxb78Zcdh2UKYd9&#10;/QXCQX2wX36KtRrvK/FT4hYRKSTGcXCOa4cz/BHMqWfD6n8Ix99F+MBg7PJfkx2eFBNK3CIihcyU&#10;LYfT7TKcwePgkObw7XzCoX0JX3wcm7E+2eFJEafELSKSJKZ2HZxrh+BcPQCq1cC+9zrhgKsIP3kX&#10;G4bJDk+KKCVuEZEkMsZgmh2NM/RBzNkXwaaN2KfHEd51E/anINnhSRGkxC0iUgSYtFI4Hbrh3DEe&#10;c3Rr+PkHwrtuInxyDPbfVckOT4oQJW4RkSLEVNsHp+eNODfdBXUaYGe/H3WfvzMFuzkr2eFJEaDE&#10;LSJSBJlGh+AMHI25oBekpGJfepJwaF/swi+THZokmRK3iEgRZZwUnBNPxxnxCKZtB/hjOeGYIWQ/&#10;OBz75/JkhydJktdlPUVEpJCY8hUx3a/Ctm5POGkCfD2HcNGX0cxrHbphSpdJdohSiNTiFhEpJkyd&#10;Bjg3jsBceRNUrIKd9hLhgF6Ecz7S7GsliBK3iEgxYozBaXECzh0PY87wYN0a7IR7Ce+5DfvrkmSH&#10;J4VAiVtEpBgypcvgnHUhzrCH4PBj4IdvCe/oR/j8eOy6NckOTxJIiVtEpBgzNWqR0qc/znVDYd90&#10;7AdvEd5+FeHMadgwO9nhSQIocYuI7AXMIc1xBo/FdLscwmzsC48Q3nE9dvHCZIcmBUyJW0RkL2FS&#10;U3FOPStafazVSfDbEsJ7+hM+dg925V/JDk8KiBK3iMhexlSuinPptTj974UGjbBffEw4sDfhmz42&#10;KzPZ4Uk+KXGLiOylTINGOLfejbn0WihdBvvac4SD+mDnf6bHx4oxJW4Rkb2YcRycVidF3eenngWr&#10;/iZ86E7CB4Zgl/+W7PAkD5S4RURKAFOuPE63y3EGj4MmzeHbrwiHXkPoP47NWJ/s8GQPKHGLiJQg&#10;pnYdnOuG4PTpD1X3wb77OuHAXoSz3seGYbLDkzgocYuIlDDGGMzhx+AMewhz1oWwcQP2qTGEI2/G&#10;Llmc7PBkN5S4RURKKJNWCucML5o+tcUJsGQx4Z03Ej41BrtmVbLDk11Q4hYRKeFMtRo4V96Ec9Od&#10;UGd/7Kz3o8VL3nkNu3lzssOT7Shxi4jI/7V37/FRVHcfxz9nAgSRgBWLsii2YkEx1jv6gHItFhBr&#10;8XKoN3yqUhEsVooFBUFAqrSKCgoq1XoXf2rRB1pRK6DipU9VbEnRAooXSFEUQQSNgZnnj9nwhJhw&#10;S3Y3E77vf9yd2Zn55bzU754zs+cA4NoUEoy6GXfOQHAB0WP3EI4dQvSvhbkuTcpRcIuIyBYuL4+g&#10;a2+CCXfguvSCj4sJbxnD5tsnEK1elevyBAW3iIhUwjVuQnDupQSjJsEP2sFbfyMcPZjwyQeJSr7O&#10;dXm7NQW3iIhUybU6iODK63EDhkHjJkR/tnj61L+/pNnXckTBLSIi2+ScI2jfieC6abjeHtavJbrr&#10;94Q3Xk300fJcl7fbqZfpC3jvjwduMLOu3vsjgcnAJqAE6G9mWrJGRCQBXH5DXN/ziDp2J3zsnnj4&#10;fPwVuM49cT89F7dnQa5L3C1ktMftvb8SmA7kpzfdAgw2s27ATGBEJq8vIiI1zzVvQd7gkQSXj4F9&#10;WxDN/wvhyIGE858mCjfnurw6L9ND5cuAvuXe9zOzRenX9YCvMnx9ERHJEFd4DMGYybizfg6bNxE9&#10;NI1w/FBKivTzsUzKaHCb2UziYfGy9x8DeO87AIOBmzN5fRERySxXrz7ByX3j1cc6dIcVy/lk+ADC&#10;6XV5DM4AABDTSURBVDcSrfk01+XVSS7TTwV67w8EHjGzDun3/YCrgNPM7IMdOIUeWxQRSYiSd4pY&#10;e+fv+GbJYlx+Q5r0u5CCvufiGuRv/2CpyFW2MeMPp5XnvT8P+AXQxczW7uhxxcXFVe5LpVLb3C/V&#10;pzbODrVz5qmNs6DJ3rS46V5WPvEg0RP3se7+qax7+k8E/iI4oj3OVZpFUkEqlapyX9Z+Dua9D4Bb&#10;gcbATO/9XO/9mGxdX0REssMFAUHHH8XD5z86DdasJrx9AuHksUSrVuS6vMTLeI87PRzeIf22Waav&#10;JyIitYNrtCeu30VEJ/UgnDEdit4kfPuXuO4/wfXph9ujUa5LTCRNwCIiIhnlUq0IrhhHMOhq2KsZ&#10;0bMzCUcNJHzleaIwzHV5iaPgFhGRjHPO4Y46gWDc7bjTzoWvNxL98VbCG35DtHxprstLFAW3iIhk&#10;jWuQT9CnH8G4abhjT4TlSwivH0Z43xSiL3b4meXdmoJbRESyzjX7LsElvyEYNgFSrYgWPBcPn//1&#10;KaJNm7Z/gt2YgltERHLGtT2c4JpbcOdcAi4gevRuwnGXEy1+K9el1VoKbhERySmXl0fQ9ZT452Od&#10;e8KqFYQ3j2bz1N8SrV6V6/JqHQW3iIjUCq6gCcF5gwhGTYKD28HC1whHDyZ86iGikpJcl1drKLhF&#10;RKRWca1aE/zmetzFv4bGBUSzHyUcfSnR6wvI9DTdSaDgFhGRWsc5R3B8Z4Lx03C9zoQv1hLe+TvC&#10;m0YRrXg/1+XllIJbRERqLddwD4LT+xOMvQ2OaA//XkQ47leED99JtGF9rsvLCQW3iIjUeq55irzL&#10;RhEMGQPNWxDN+3P887EX5hCFm3NdXlYpuEVEJDHc4ccQXDuZ4MyfQ+kmogenEk74NdGyxVWuPFbX&#10;ViTL6rKeIiIiu6q0NGLJkvXMnbuSoqLmtG87lNPdizRZ/BLhxBG8RjvePvSnHP/jdhx0UGPee+/L&#10;9GfXUFi4N926taRNmwLq1092kCu4RUSk1istjZg16yOGDFlA2YPl77+/Nxv79OG5V/MZ2+4N2jdd&#10;zGGLljDlyXZ8/+L+3PfQexQVrQFg9uwPmDhxIZMnn8ippx6Q6PDWULmIiNR6S5as3yq0Ac46qzUT&#10;Jy7kjc/34dSXT+bKfx7HV5vzGNH2nxw/51qu6F4C/P8BUQRDhixgyZJkP9Sm4BYRkVpv7tyVW4V2&#10;KtWIDz/8csu2CMejK1rT5YVT+MPyNuy/xwZ6LL2bGSe+zPf3/GLLcVEE8+atzHL1NUvBLSIitZpz&#10;bsuQd5n99ouDu6IvNjVg3NtH8+MFPVkctqJDkxU8d9Icrm77Fo3rlQJQVPR5oh9YU3CLiEitFkUR&#10;hYV7b7Vt1aqNtGrVuMpjln7ZlMdSFzJieTdWfb0HA1u/w/xOf+b01HIKD2ua6BnYFNwiIlLrdevW&#10;kvKd5OLiOLir6jg7Bwe0KuDht5vT/cVe3LSkkCb1S7nlyL9xwep7iN5fmp3CM0DBLSIitV6bNgVM&#10;nnziVkH92GPvMnz4Ud8Kb+dg4sT/4vHH3wWgJKzHrcsK6fZib1budxSN/rOU8LfDCO+/jeiLtVn8&#10;K2qGfg4mIiK1Xv36jlNPPYC2bfswb95Kioo+p7DwO/TosT9du6aYP794y7auXVty0EGNOfLIZlt9&#10;tmvXlrRoU0Dw7iLCGdOJXnqW6PWXcT85G9elN65eMiLRJWCcPyouLq5yZyqVYlv7pfrUxtmhds48&#10;tXF2ZKOdnXPfuk9d2baqtkebNxO98DTRUw/Bxg2QakXwswG4Q4/IaN07KpVKAVR6I0BD5SIikjiV&#10;BXRVHdFKwzwvj6BbH4Lr7sB16gn/+Yhw0jVsnnYD0acf13i9NUnBLSIiuy1X0JTg/EEEIydB60Pg&#10;zVcIRw8m/J+HiUpKcl1epRTcIiKy23MHtiYYPhF30VBo1Jho1gzC0YOI3ni51v10TMEtIiJCfC88&#10;OKELwXVTcb3OgHWfE94xkfCmUUQrP8h1eVsouEVERMpxDRsRnH4Bwdjb4IfHwb8XEY67nPCRu4g2&#10;fHu2tmxTcIuIiFTC7Zsi75fXEAwZDfvsRzR3NuGogYQvPkMUbs5ZXQpuERGRbXCHH0tw7RTcGRdA&#10;aSnRA7cTThhGtOztnNSj4BYREdkOV78+Qc8z4vvfJ3SFD98lnDic8O5JRGs/y2otCm4REZEd5PZq&#10;RnDRFQTDJ0Kr1kSvzSccdSnh008QlZZmpQYFt4iIyE5yBx9KMPJGXP/LoH4Doj/dR3jtL4kWvZ7x&#10;ayu4RUREdoEL8ghOOjmefa37qfDpKsLJ49g8eRzRx5mb8jUZM6qLiIjUUm7PxrifDSA66WTCGdNh&#10;0euEi9/C9TgNd8pZuIaNavR6Ge9xe++P997Pq7Btkvf+F5m+toiISLa4lgcSDB1PMHAENP0O0Zwn&#10;CEcNInxtXo3OvpbRHrf3/krgfODL9Pt9gPuBHwDvZPLaIiIi2eacg2M6EBQeQ/TMn4jmPEF0981E&#10;858mOPsS3IGtq32NTPe4lwF9y71vDIwBHsjwdUVERHLG5ecT/ORsgvFT4egO8O47hBOGEj5wO9H6&#10;ddU6d0aD28xmApvKvX/fzP5OFWuMioiI1CWuWXPyLh1BMHQ8tDiA6MVn4tnXnp9NtHnXZl9LxMNp&#10;6QXFd3m/VJ/aODvUzpmnNs4OtXMFqRRR5x58+ZfHWffgHUQz7qLeq8+z1yXDaHjEcTt1qmwFd7V6&#10;2MXFVT9Wn0qltrlfqk9tnB1q58xTG2eH2nkbju2Ea3sEzHyA0gXPsfrqS+N74mddiGvWfMvHtvXF&#10;J1u/4674OF3tWtxUREQkS1xBU4L+lxGMvAlaHwJvvEI4ehDhrBlE35Rs//jatkB4JSL1uHNLbZwd&#10;aufMUxtnh9p5x0VRRPS3+USP3wfr1kCz5gT+Qlr2OROqGK3WzGkiIiI54pwjOKFrvHjJj0+HtWsI&#10;p92wzWMS8XCaiIhIXeYaNsKd+d9EJ/Yg+ott87MKbhERkVrC7dcSd+EV2/yMhspFREQSRMEtIiKS&#10;IApuERGRBFFwi4iIJIiCW0REJEEU3CIiIgmi4BYREUkQBbeIiEiCKLhFREQSRMEtIiKSIApuERGR&#10;BFFwi4iIJIiCW0REJEEU3CIiIgmi4BYREUkQBbeIiEiCKLhFREQSRMEtIiKSIApuERGRBFFwi4iI&#10;JIiCW0REJEEU3CIiIgmi4BYREUkQBbeIiEiCKLhFREQSRMEtIiKSIApuERGRBFFwi4iIJIiCW0RE&#10;JEEU3CIiIgmi4BYREUmQepm+gPf+eOAGM+vqvW8N3AuEQJGZDc709UVEROqSjPa4vfdXAtOB/PSm&#10;ScDVZtYZCLz3p2Xy+iIiInVNpofKlwF9y70/xsxeSr9+GvhRhq8vIiJSp2Q0uM1sJrCp3CZX7vV6&#10;oGkmry8iIlLXZPwedwVhudcFwNodOSiVSlVrv1Sf2jg71M6ZpzbODrVz5mQ7uN/03ncysxeBXsDc&#10;HTjGbf8jIiIiu4dsB/cwYLr3vj7wNvB4lq8vIiKSaC6KolzXICIiIjtIE7CIiIgkiIJbREQkQRTc&#10;IiIiCZLth9NqRIVpVL9LPDvbXkAe0N/Mlue0wDqgQhsfCUwDSoElZnZxbqtLNu99PeAe4HtAA2AC&#10;sBhNB1yjqmjnD4EpxPNLlBD//2J1rmpMusra2MxmpfedA1xmZh1yV2HdlLgedyXTqP4OeNDMugDX&#10;AIfkqLQ6o5I2Hg1ca2adgIbe+1NyVlzdcB7wabo9ewK3oemAM6Gydr4FGGxm3YCZwIgc1lcXlG/j&#10;XsRtjPf+KODCXBZWlyUuuPn2NKodgf29988B5wDzc1FUHVOxjRcC+3jvHfHEOaU5qaruMOIvmRCP&#10;Em0CjtZ0wDWuYjuXAv3MbFF6Wz3gq1wUVoeUb+MAKPXe7w1cB1yes6rquMQFdyXTqH4PWGNmPYCP&#10;0DfoaqukjZcCk4F/Ac3Rl6NqMbONZrbBe18APAaMRNMB17jK2tnMPgHw3ncABgM357LGpKukja8B&#10;7gaGAhvQBFoZkbjgrsRnwKz061nAMTmspa66FehoZu2AB4iHdaUavPcHEM8ceJ+ZzWAXpwOWbavQ&#10;zo+mt/UDpgK9zeyzXNZXF5RvY+LRuoOJn4l5BDjUe6//X9SwRD6cVsFLQG/gIaATca9QatZnxL1A&#10;gGJAD5tUg/d+X+AZ4nut89KbF+7CdMCyDZW1s/f+POAXQBcz05ejaqri3+XD0/sOBB4xs6G5qq+u&#10;qgvBPQz4g/f+UmAd8X1uqVkDgEe996XAN+n3suuuIv4VxDXe+9FARHw/cIqmA65RFds5DzgM+ACY&#10;6b2PgBfMbGwOa0y6yv5d7mVmJbktq27TlKciIiIJUhfucYuIiOw2FNwiIiIJouAWERFJEAW3iIhI&#10;gii4RUREEkTBLSIikiB14XfcIonivQ+AXwFnE/+2uAEwGxhtZt/swvn+CCwysx2aocp73x24kfg3&#10;ty3SNaxI776eeEKjHT7fTtbaGbjNzA7fyeNCYB8zW1Nh+6+BQjP7eQ2WKVKrKbhFsu8O4rnIu5nZ&#10;eu/9HsDDxCuyXZDpi5vZ88BRAN77MUAzMxtStt973zvDJezK5BHbOkaTUchuRcEtkkXe++8R97T3&#10;M7MNAGb2lff+EqBDOsRXAu3NbFn6mGeJ15Cem/5nR+KVrp40s1EVzn8o8dKVexP3pCeb2b27UGpH&#10;7/0ZwL5AEXB2us6vgaeAHwLnAhuJ57Lf6nre+z2BPxLPWx0Cb5jZJelzF3jvHyFegjcfGGBmL3vv&#10;mwC3A0emj5kDXGVmIenFKtLrP08hXj3tY+ATNK+77GZ0j1sku44G/lUW2mXM7BMze9LMvgLuJT2t&#10;rPe+NdCGeCh9PJBvZm2Je8wdvfedys7hvc8jXqFpuJkdB3QBrvTet9+FOlNAt/S19wdOT29vADxl&#10;ZocC/yCemrWy6/UFGpvZ0UD7dH0Hpc/RErjJzI4C7gKuTW+fQry28+HAscARxFMalzeY+MvAIcDJ&#10;QKtd+NtEEk3BLZJdIdv/724acH46iAcA080sAroTL5mImZWaWdf0oiRl2gCtgXu89wuBF4CGpIfF&#10;d9KTZlaS7u0WES/nWmbBDlxvAXCY934e8VK7t5jZe+nj3jWz19Ov3yp37p7AbWV/H/EthV7pfWXD&#10;4d2Bh81ss5ltJF5cSGS3oqFykez6X+KlDvcs3+v23rcE7gTOMLOl3vt/Aj8lHo4+Nv2xTZS7n+u9&#10;3594qLpMHvB5updb9pnm7NpQcmm51xFbr6v85fauZ2bfeO8PJu6FdwOe995fRrzSXFXnrviFJgDq&#10;V9hWsZZNiOxm1OMWySIzKybuJd7jvS8AKHdvd3W5VZWmAr8HXjOzj9Pb/gpc4L133vt84mHqTuVO&#10;/2/ga+/9uenzHkDcW87UGvVVXs97PxC418yeM7OriJd+LEwf5yo9W3p5yPS58omX33y2wjFzgP7e&#10;+3zvfUOgXw3/TSK1noJbJPsGES/d+Yr3/k3gVeLAK79c6mygMfGweZmxxL3VfwBvALPN7Mmynenh&#10;5dOAi733/yAOuZFm9upO1lfxKe2ostfbud79QOC9X+y9/ztQQPwQW2XnLzME2Nd7vyj9N74D/LbC&#10;MXcS/+1FwDzgvYonEanrtKynSC3kve8A3Lmzv3cWkbpP97hFahnv/b1AZ+D8HJciIrWQetwiIiIJ&#10;onvcIiIiCaLgFhERSRAFt4iISIIouEVERBJEwS0iIpIgCm4REZEE+T/ut5NePjo8gAAAAABJRU5E&#10;rkJggg==&#10;">
+
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAe4AAAGMCAYAAAAcK0EHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz&#10;AAALEgAACxIB0t1+/AAAIABJREFUeJzs3XmcTuX/x/HXdWbGvouYLEk5kZJKKkW0KJESp9Je9A2l&#10;tCd7FC0KlYr2hU6L+iqlhTYqUQrVUd+kBW3IMpgx5/r9cW5+Yxu3mbnnnjHv5+Mxj3Gf5Tqf+5ox&#10;n/u6znWuy1hrERERkeLBSXYAIiIiEj8lbhERkWJEiVtERKQYUeIWEREpRpS4RUREihElbhERkWJE&#10;iVtERKQYSU12ACKFyXXd1sAHwCNBEPTOsf0S4N4gCGok4JptgJlAhSAIMuI4/lCgehAEH+TjmpWA&#10;W4CuQF1gBfAGcGcQBCvyWm4e4tgHOCUIgkmx1zOBL4IguNl1XQM8CXQD/gSGAPcEQVCzAK67TR26&#10;rhsCHYMgmJbfsndyrdLAHcC5QGVgDnBdEATfFvS1REAtbil5LgAWA+fF/uDmlMjZiPak7NeBJnm9&#10;UCxZfg60AXoDLnBZ7Ptc13Ub5rXsPLgbODvH67OBobF/HwtcHNvWCphMPt73dravw1rAuwVU9vZG&#10;AV2I3ksLog9J77iuWyFB15MSTi1uKTFc1y1F1AK9DngUOAd4IalB7ZzJ5/kPAKuBNkEQZMe2/eq6&#10;7kfA28DjwIn5vEa8tnkvQRCszvGyKmCDIHgnx7ZNCbrunwVU7jZivQaXAFcGQfBhbNsVwCqgHfDf&#10;RFxXSjYlbilJOgKVgDeJuq4vZ7vE7brubcANsZfPADcGQRC6rptClBC7EnWHzgOuD4Lgi9h5DYF7&#10;iVq5IfBqbP+67cqvDywBmm7pSs3ZTR/rSq4PjHNdt2sQBO1c190XGAecBqyLxX9DEARrtn+DrutW&#10;Jep6PjtH0gYgCALruu5gYLbruo2DIPjOdd0lRN3TD+8sPtd1awL3A6fE3vevwIggCJ6MHT8T+BA4&#10;HDgV+BsYEgTBE7FrXRI7LjsIgpQtXeXAIqJuclzXzSZqhS8lx+0K13UPA+4DjgFWAuODIBgZ29cC&#10;uAtoSfR37GugbxAEc3ZRh1u7yl3XTQP6x2KrDcyN1eecXN7T0CAIHt++vol6LbsS/T5sEca+V9nJ&#10;8SL5pq5yKUkuAGYFQbCSKLGeGEtUW+xD9If6xNix3YGbY/uuAToBZxJ1wS4GXgJwXbcK8AlRa7EV&#10;Udfv8UQt253ZWbf5lm1dgN+IEkuX2LYpQDZRkuoIHEDUrbwzRxIlsk93tjMIgs+AjcBxuzh/+/ie&#10;JaqXtkBjoi7o8a7r5hwLcDMwjahepgAPx/bfC/jAVKKu6pwmAxfFrlUrduzWa7uuWx14n6gujgKu&#10;BG51XffSWBf0NOBL4FCiellH1IsCO6/DnB4k+tDWiyg5LwLejX1A2tV7emi79wxAEATZQRC8v11P&#10;wlVAKaKxFCIFTolbSgTXdSsDHYBXYpteI2oZXZrjsM1A9yAIFgZBMB0YTnSPGGB/ooT3axAEPwPX&#10;A5fEukovJPq/dHEQBN8FQfBxrNxuu7ifvMuu8CAIVhEl6bVBEKx2Xbct0BS4KFb2l0QJ7zTXdRvv&#10;pIh9Yt/X7uoaRK3XfXLZnzO+qcB/giBYFATBT8CdREmpUY5jZgZB8FisXgbE9jcLgmA9sAHYFATB&#10;X9u9z01E3fkEQfDXTgbtnQdkAj2DyHSiRLsOKEd0X/nWIAh+DoLgG2A8UT3tUIc5C439HlxONHhs&#10;ehAEQazcX4Grd/eecqmzLeW3Ae4BRgVB8MvujhfJCyVuKSnOJfrjOwUgCIJ/iLpDL8lxzO9BECzP&#10;8XoesF9shPZ4oALRveKPgf8A3wZBYIlaovODIMjMce4XRInnkHzG3QQoD6xyXXet67prgYDoQ8fB&#10;Ozn+n9j3OrmUWZlY0ozDeOAY13XHuq77NvAtUas4JccxP2z5RxAEWz4wpMVZ/q40Br4JgmBzjrIn&#10;BUHwcux+9USgj+u6E2P37p8mvr9njWLHfZajXAvMZtuf1R6/J9d1TyO6jTElCIKBccQikie6xy0l&#10;xQWx70tc192yzQDGdd2TYq+ztztnSyLICoIgcF23AdAeOB3oC1ztum5Lopb4zhi2TXCw827y3P4f&#10;pgI/AyezY0v9j50cP5eo5+Do2HnbcF33SKIPAl/sIp7UHMcaYDqQTtS1PYOoWznY7pxMdpTfAXaZ&#10;uyrDdd3aRI9cfQ+8FYutBvBcHOVu3EW5Dtv+rPboPbmu6xHdVphENIJfJGHU4pa9nuu69YjuOQ8m&#10;6u7c8nUkUdfr5bFD68TuV29xHLA0CIINruteCJwbBMEbQRD0IXq0qmas3O+Aw7d7vOxooiT43Xbh&#10;bEkIFXNs2747PWcy/Y4oca4LguCnWHd1NtFAuR2ed451E/vA4NggLFzXbeW67jeu63Yket54XqzL&#10;fUs828ey5frNiUZGnx4EwbAgCF4jGgkO8SfmvD5itxhoGhsUSOx9DHJd90XgfKIPU6cEQTA6CIL3&#10;iJ5Vj+e6PwJZ7HiP/1ii3oQ95rruqUQfGp4IguDSWAteJGHU4paS4EKie61jtx+J7bru00APohZo&#10;KjDJdd1biBLYbUSTmEA0Gn2Y67r/EP2B70iUvL4ElgGDgGdc1x0GVAceBt4NguD72KCnLYnuD6L7&#10;qTe4rnsr0QeIS7eLdx3QODYY6t3Y9V50XfdGoi7yB4m67X/exfu9jug2wEzXdYcC/wNmET2aZNk2&#10;aX0BXBzrBi9DlNi3JJ4VxO77u677PNGHlTGx/ds/A78r64BDXNetHwTB0jjPAXieaEKWh13XvQ84&#10;MPa+riX6sLGv67pnAAuJBs7dDtEjf7FbFlvrMOf99diHsHHAaNd11xONoL+WaBT6hD2Ij9j1SgNP&#10;EdXv0O0GuK0JgmDDnpYpsjtqcUtJ0B2YvLPHp4iSYCmiEeHfEiWyj4ju7d4bBMEEgNjjUg/Gtn9P&#10;NMq5axAE/4v9cT6V/5816yWiEcXn5LiOjZVjiRJ1Y6Ju52uJPiDkNIbow8bbsePPJLp3PSP2tQzo&#10;sKuWXez+/bGxGB4kSm4diR5vexWYHGt9Q5Twficahf4UUa9EGCtnWex99iRq+T8APAR8Q9RbsSs5&#10;43qK6JGrRbFHy+ISu698OtF9/Pmx6w4NguBZoh6FCUSPk30di69H7Lpb4tpahzuJ6Tbgxdj584h+&#10;FifGejO2P3Zn7ymn44F9gdZE9bgsx5e6zCUhjLWJ7dXxPK8lMNL3/bae5x1O9IcvC1js+36PhF5c&#10;RHYQ69rNCoJgZrJjEZE9l9AWt+d5NxF9Mt7SrTYIGOL7fmugjOd5ZyTy+iKyoyAI3lHSFim+Et1V&#10;/iPbzlP8FbCP53mGaEBMVoKvLyIisldJaOL2fX8K0eCWLX4AxhLd26uJZhYSERHZI4U9qnwM0Mr3&#10;/e89z+sNjGbb2Yp2Ro9WiIhISbTTxy4LO3H/w/9PxbiM3OdL3mrZsmW73Jeenp7rfsk/1XHhUD0n&#10;nuq4cKie8y89PX2X+wo7cfcEXvQ8L4vYPMSFfH0REZFiLeGJ2/f9pcRa1r7vzyJ67lFERETyQBOw&#10;iIiIFCNK3CIiIsWIEreIiEgxosQtIiJSjChxi4iIFCNa1lNERIqF+fPnM2zYMPbff38A1q9fT3p6&#10;OgMGDCAlZevS7VhrGT9+PEuWLCEzM5OyZcty7bXXUrt27d1eIzMzkxEjRrB69WrKlSvHrbfeSuXK&#10;lbc5ZtKkScyYMYPy5ctz7rnncuyxx7J27VpGjBjBhg0bqFSpEjfeeOPW87Kzs7njjjs444wzaNGi&#10;Rb7rQS1uEREpNpo3b87o0aMZPXo0jz76KCkpKcyaNWubY+bMmcM///zDPffcw5gxY+jUqRMPP/xw&#10;XOW//vrrHHDAAYwZM4ZTTjmFZ599dpv9S5YsYcaMGYwfP567776bJ598kszMTJ5//nkOO+wwxowZ&#10;w1lnncWECdHy7suWLeO6664jCIKCqQCUuEVEpJjKyspi5cqVVKxYcZvtVapUYfHixcycOZN///2X&#10;Vq1aMWTIEAA+/PBDevbsyU033cSQIUOYPn36NucuWLCAo48+GoCWLVsyb968bfYvXbqUww8/nNTU&#10;VEqVKkWdOnX48ccf+fnnn7eed+ihh7JgwQIANmzYwE033cThhx9eYO9bXeUiIrLHwpeexM6btdN9&#10;y1JSyM7O3uMyzZGtcLpdlusxX331Fddffz0rV67EcRw6depE8+bNtznGdV1uuOEGpk6dyrhx46hZ&#10;sya9e/fmkEMOYfz48UycOJHy5ctz66237lB+RkYG5cuXB6BcuXJkZGRss/+AAw7ghRdeYMOGDWRm&#10;ZrJo0SI6derEQQcdxOzZsznwwAP55JNP2LRpEwANGzbc43rYHbW4RUSk2NjSVT527FjS0tKoVavW&#10;Dsf89NNP1K1bl4EDB/Lqq6/So0cPhgwZwpo1a6hUqRIVKlTAGEOzZs12OLdcuXJs2LABiJJ4hQoV&#10;ttlfr149zjrrLG655RbGjRtH48aNqVy5Mt27d2f58uVcd911/Pnnn9SsWTMxFYBa3CIikgdOt8tg&#10;F63jwlhkpFKlSvTv359+/foxceJEqlWrtnXfvHnzWLp0KTfccAPGGOrXr0/ZsmWpWrUqGzduZPXq&#10;1VSpUoUgCDjuuG3XumratCmfffYZruvy+eefc+ihh26z/99//yUjI4OxY8eyfv16br75Zho0aMDn&#10;n39Op06daNKkCR999BFNmzZN2HtX4hYRkWKpfv36nHPOOYwbN47Bgwdv3d6lSxceeeQRevTosbV1&#10;ffvttwPQr18/+vfvT/ny5bd2Z+fUuXNn7rrrLvr27UtaWhoDBgwA4KWXXqJOnToce+yx/PLLL/Tq&#10;1Yu0tDSuuuoqjDHUrVuXu+66C4AaNWpw8803J+x9G2uL/HLXVst6JpfquHConhNPdVw4iks9T5gw&#10;gXr16tG+fftkh7KD2LKeO12PW/e4RUREihF1lYuISInUs2fPZIeQJ2pxi4iIFCNK3CIiIsWIEreI&#10;iEgxosQtIiIJYS1kZGSzeXORf3qpWFHiFhGRApWZmcWiRWsYMeJrzjzzHbp3n8n06cv4++/MAr/W&#10;lClT8l1Gnz59+OOPP/b4vF9++YV+/frl+/p7SqPKRUSkQE2Z8j0XXPAO2dn/39KeNWsFp5xSh7vv&#10;bknNmqUL7FrPPfccZ599doGVt6eM2emj1gmlxC0iIgXmt9820KPHjG2S9hbvvvsbs2c34Kyz6uax&#10;7N8YNWoUqamphGHIEUccwdq1axkzZgw9e/bknnvuYf369fzzzz907tyZM888k379+nHggQeyZMkS&#10;MjIyGDJkCDVr1mTixInMnTuXGjVqsGbNGgD++usvHnjgATIzM1m5ciWXX345rVq14vLLL6dOnTqk&#10;paXRp08fhg8fDkDVqlW3xjZx4kTmz59PGIa0bt2a8847L0/vMR5K3CIiUmAWL/6Xdeuydrl/3LgF&#10;nHxyOhUqpOxx2XPnzqVx48b85z//YcGCBVSuXJmpU6dy7bXX8sMPP3DSSSdx/PHH888//9CvXz/O&#10;PPNMABo3bkyfPn14/PHHef/99zniiCNYsGABjzzyCBkZGVx00UVA1PXteR7NmjVj0aJFPPXUU7Rq&#10;1YoNGzZwySWX0LBhQ8aOHctJJ53EGWecwcyZM5k6dSoAM2bM4P7776datWo7LBVa0JS4RUSkwKxd&#10;u+ukDfDHHxvYuDE7T4m7Q4cOTJo0iZtvvpkKFSpwxRVXbN1XtWpVXn75ZT766CPKlSvH5s2bt+47&#10;8MADgWgO8VWrVvHbb7/hui4QrQbWoEEDAKpXr86zzz7LtGnTALZZmrRu3aiX4Ndff6Vjx45AtCDJ&#10;lsTdv39/HnvsMVatWrV1Xe5E0eA0EREpMDVrls11/2GHVadChby1GWfNmsVhhx3GfffdR5s2bZg0&#10;aRJb1tvwfZ9DDjmE/v37c+KJJ5JzHY7t70PXr1+f77//HoANGzawdOlSAJ544gnat2/PbbfdRvPm&#10;zXdaxv7778/ChQsBtpaxefNmPvzwQwYOHMjo0aN5++23+fPPP/P0HuOhFreIiBSYRo0qUb9+BZYu&#10;XbfT/b17H0KZMnlrM7quy8iRI3n22Wex1m4dDX7nnXfSoUMHxo4dy8yZMylfvjypqalkZWXtdPDY&#10;gQceyNFHH81VV11F9erVt96rPvHEExk/fjwvvPAC++yzz9Z73znLuPDCCxkxYgQffPDB1rXAU1NT&#10;qVixIr1796ZMmTK0aNEioetxa3Uw2S3VceFQPSee6rhw/PxzJl27TmP58oyt24yBwYOP4oILGlKu&#10;3J53k5c0ua0Opha3iIgUqGOPrc8bb5zOd9+t5vvvV1G1ahkOP7w6BxxQnlKldIc2v5S4RUSkQBlj&#10;qFWrNLVq7UvbtvsmO5y9jj76iIiIFCNK3CIiIsVIsUjcduGXyQ5BRESkSCgWiTscM4Tsh0Zg/1qR&#10;7FBERCROxlpSMzJwckyGIvlXLBI3BzWB+Z8TDupDOOU57KaNyY5IRER2ITszk3KLFlFlxAiqn3km&#10;1bt3p8L06ZT6++98lZuZmcmbb765R+d88803LFmyJF/XLWoSPqrc87yWwEjf99t6njcJ2Jfo2bT9&#10;gU993+++uzKcm+7CfvEx9qUnsdN87KczMF0vxbQ4IbHBi4jIHts0ZQqVL7gAE5syNAVImzWLzFNO&#10;Yc3dd5OZx8lJVq5cybRp0zjjjDPiPuett96ibdu2W6c13RskNHF7nncTcBGwDsD3/fNj26sAM4Dr&#10;4inHGIM5ujW22dHYaS9j33kVO+Fe7AfTyOw7AMpUSNRbEBGRPVD6t98o26PH1qSdU6l336X07Nlk&#10;nnVWnsp+7rnnWLp0KU8//TRLlizZOrPZNddcQ4MGDRg1ahTLli0jMzOTLl26UL9+febMmcMPP/xA&#10;gwYNqFGjRr7eW1GR6Bb3j8DZwLPbbR8KjPN9f48mczWly2DOvhDb6iTCl56A+Z/zx7UXYlqfhunc&#10;HVOhUkHFLSIieZC2eDFm3c6nOwUoO24cG04+mc0V9rzBdeGFF7JkyRIyMzM54ogjOPPMM/n9998Z&#10;NWoUo0aNYsGCBTz00EMAzJs3j0aNGnH00UfTrl27vSZpQ4ITt+/7UzzPq59zm+d5NYB2xNna3hlT&#10;szYpfW7HLpyH88pTbP5gGvaLjzFnXYBp3R7jaDo9EZFkMGvX5rrf+eMPnI0bIQ+Je4uffvqJL7/8&#10;kg8++ABrLWvXrqVs2bL06dOH++67j4yMDE4++eQ8l1/UJWPmtK7AC77vxz1JemzO1p3twLY9jbVT&#10;X2TNCxOwzz9C6uwZVLnqRso0PaKAwhXI5WcgBUr1nHiq48TK2G+/XPdnN2tG5Xr1SKtSZY/LNsaQ&#10;mppKkyZNaNq0KWeccQYrV67k5ZdfJi0tjeXLlzNx4kQyMzM58cQTufTSSylfvjxVqlTZq37uhZW4&#10;c06UfjJwx56cvLtFRtYd0w7TuDm8+gxZs9/nr1uuxLQ4AdP1Mky1ffIYsmyhhRkKh+o58VTHiVeq&#10;QQNK169PSmypzO1t6NWLdRkZkJGx0/25yczMZMOGDfz5559MmTKFZ555hoyMDC699FKysrJYunQp&#10;Xbp0ISUlhW7durFixQrq16/PqFGjKF26NPXq1cvv2ys0uX3QKKzEnbN13Qj4qaAvYCpXxVx2LbbN&#10;aYSTHotGoX89B9OhG+bUszBppQr6kiIisp3M6tXZ9MILlOnaFWf58q3brTFkDB7MhiPy3htaqlQp&#10;HnvssV3u79ev3w7bOnXqRKdOnfJ8zaJor1zW04Yh9tMZ2FeehrX/Qo1aON4V0Ozona7NKrlTK6Vw&#10;qJ4TT3VcOGrXrs0/X31Fqe++I+X777FVq5J1+OFsOuAAwlJqRMWjxC3raRwH0+pkbPNjsVMnY2e+&#10;QfjQCDikOc65PTG16yQ7RBGRvZYxhsxatcisVQvatk12OHud4jFzWh6ZcuVxzr0CZ9AYaNwMFn1F&#10;OPQawpeewG7Y8/srIiIiybZXJ+4tTHo9nH7DcHr3hyrVse+8RjjgKsJZ72PDMNnhiYiIxK1EJG6I&#10;zb7W/BicYQ9hOl8AGzOwT40hHHkzdskPyQ5PREQkLiUmcW9hSpXG6XguzrDxmKOOhyWLCe+8gfCp&#10;sdg1q5IdnoiISK5KXOLewlSvgfOfm3FuHAH71cfOeo9wQC/Cd1/Hagk6EREpokps4t7CuIfiDHwA&#10;0/0/YBys/zjhsGux336V7NBERER2UOITN4BJScFpewbO8EcwbU6DFb8R3j+Y7IfuxP61ItnhiYiI&#10;bKXEnYOpWAnnwt44A0bDgU1g/meEg/oQvvYcdtPGZIcnIiKixL0zpl5DnJvvwvS4ASpUxL7pEw7q&#10;TfjFJxSDmeZERGQvpsS9C8YYnJZtcO4Yjzm9K6xZjX3sbsJ7b8f+tiTZ4YmISAmlxL0bpkxZnC4X&#10;4wx9EJodDYsXEg7rR/jCI9j1ua87KyIiUtCUuONkaqaTcvUAnL6DoWZt7Mxp0exrH7yFDbOTHZ6I&#10;iJQQStx7yBx6JM6QsZiul0HWZuzz4wmHX4/94dtkhyYiIiWAEncemNQ0nPZn4wwfjzm2Lfy6hPDu&#10;Wwkn3Idd9U+ywxMRkb2YEnc+mCrVcC7vh3Pr3VD/QOycDwkH9iKc9hI2KyvZ4YmIyF5IibsAmIYH&#10;4/S/F3Px1VCqNHbKs4SD+2C/nqPHx0REpEApcRcQ4zg4J5wadZ+ffCb88yfhg8MJxw7Frvgt2eGJ&#10;iMheQom7gJlyFXDO7YEzeCw0bgYLvyQccg3hS09iN2QkOzwRESnmlLgTxKTXw+k3DKfXrVClOvad&#10;KdH979kzsGGY7PBERKSYUuJOIGMM5ojjcIY9hDmzO2Ssxz75AOGoW7A//5Ds8EREpBhS4i4EplRp&#10;nE7n4dzxMObIVvBTQHjnjYRPj8OuWZ3s8EREpBhR4i5EpnpNnKtuwblhOKTXw37yLuGAXoTvvY7d&#10;vDnZ4YmISDGgxJ0E5uDDcAY+gDn/SjBgX3yccNi12G/nJzs0EREp4pS4k8SkpOC064gz/BFM69Ng&#10;xW+E9w8ie/xd2L//SHZ4IiJSRClxJ5mpWBnnot44t4+GhgfDl58SDupD+PoL2E2bkh2eiIgUMUrc&#10;RYSp3xDnllGYK66HchWwb0wmHNQLO/cTzb4mIiJbKXEXIcYYnGNOxBn+MOb0c+Df1YSP3k143wDs&#10;bz8nOzwRESkClLgTwBiTv/PLlMPpcgnO0AfhsBYQLCC84zrCSY9h16/LV0z5jU1ERJIrNdkB7C2y&#10;siyLF69lxozfWbhwJU2bVqNdu/1o1KgiaWl5S5Zm33RSrhmIXTCXcPJE7Iw3sHM+xJx9Eeb4UzBO&#10;SlwxzZ//N+XKpbF48Wp+/HENhx2W/9hERCQ5TDG4f2qXLVu2y53p6enktr8wZGVZpk79lb59PyFn&#10;dRoDY8ceT6dOdfOdIG1WFvb9/2Lf8GHTBqh3AM75V2IObJJrTI8++i0dO9Zn1Kiv8hxbUajjkkD1&#10;nHiq48Khes6/9PR0gJ3+cVZXeQFYvHjtDkkbwFro2/cTFi9em+9rmLQ0nNPOie5/H9MWfvmJcNSt&#10;hBPvw676Z5cxdevWcIekXdCxiYhI4VHiLgAzZvy+Q2LcwlqYOfP3AruWqVId54p+OLeMgnoNsZ9/&#10;GC1e8tYr2KysbWKqXbscv/yyrtBiExGRxEv4PW7P81oCI33fb+t5Xg1gAlAFSAEu9n1/SaJjSCRj&#10;DAsXrsz1mIULV2GMKdDHusyBjXFuvxc7633sq89gX30a+8k70ZKizY5m4cKV1KoVJe7Cjk1ERBIn&#10;oS1uz/NuIkrUpWOb7gae833/RGAgcHAir18YrLU0bVot12OaNq2akMRonBScE06NZl87qRP8/Qfh&#10;uDvYPGYorQ7KZsWKDOrVq5CU2EREJDES3VX+I3B2jtetgDqe570LdAc+SPD1C0W7dvuxq6esjIG2&#10;bfdL6PVN+Qo45/XEGTQGDj4MFsyl+w/3c0ml2RywX2pSYxMRkYKV0MTt+/4UIOeyV/sDK33fPwX4&#10;Fbg1kdcvLI0aVWTs2ON3SJDGwLhxJ9CoUcVCicPsVx/n+jtwrroVqlSj1wHf0+GzETx+pcWYbVvV&#10;hR2biIgUjMJ+jvsfYGrs31OB4YV8/YRISzN06lQX1+3IzJm/s3DhKpo2rUrbtoX/rLQxBo48jpSm&#10;R7L5rVep+vbLnPzri3x1fgPerNiBT3+vUCDPmIuISHIUduL+GOgAPA+0BhbFc1LsebY87y8s9evD&#10;SSc1IgxDHMfBcZI8aL/3DWzu2p1VE++n2qwZXPTvw1x5yplUvrg3aVWr71FRRaWO93aq58RTHRcO&#10;1XPiFHbivhGY6HleL+Bfovvcu1XUJ2Ap8i69DqdlW8LJE9jwzuts+Pg9TOfumDanY1J3/yugOi4c&#10;qufEUx0XDtVz/uX2wUczp5UgdvNm7IdvYV9/ATash/R6OOf1xDRulut5quPCoXpOPNVx4VA9559m&#10;ThMATGoqzkmdcEY8gjnhVFj+K+HogWSPH4n9+49khyciInFQ4i6BTMXKOBdfjXP7fdDwYPhyNuGg&#10;PoT/nYTN3JTs8EREJBdK3CWYqX8gzi2jMFf0g3IVsFMnEQ7qg503W5OyiIgUUUrcJZwxBueYttHi&#10;Je27wOqVhI+MJBw9EPv7L8kOT0REtqPELQCYMuVwul6KM2QcND0Svv+GcFhfwskTCNeuSXZ4IiIS&#10;o8Qt2zC19iPl2sE41wyEffbFvj+V5Vd2IfxoOjbMTnZ4IiIlnhK37JQ5rAXOkAcxXS7BZm7CPvsQ&#10;4Z03YX/8LtmhiYiUaErcsksmLQ3n9HOo/dirmGNOhKU/Eo66hfDx+7Gr/0l2eCIiJZISt+xWSvUa&#10;OFdcj3PLSKh3APazmYQDehO+/Qo2KyvZ4YmIlChK3BI3c2ATnNvvw1zUG9JSsa88TTjkGuyCuckO&#10;TUSkxFDilj1inBSc1qfhDH8U064j/L2CcOwwsscOw/6pKQ5FRBKtsBcZkb2EKV8Bc/6V2BNOJZw8&#10;ARbMJfzeBNdYAAAgAElEQVRuPuaUzpgOHqZM2WSHKCKyV1KLW/LF1Nkf54bhOFfdApWqYt96hXBg&#10;L8LPPtDsayIiCaDELflmjMEc2Qpn2MOYjufBurXYx0cT3n0rdun/kh2eiMheRYlbCowpXRqnc3ec&#10;YQ/BEcfCj98Rjrie8NmHsGv/TXZ4IiJ7BSVuKXCmRi1Set2G028Y1KqD/Wg64YCrCN9/A5ut2ddE&#10;RPJDiVsSxjQ5HGfQGMy5PcCCnfwY4R3XYb//JtmhiYgUW0rcklAmNRXn5DNxho/HnHAqLPuF8L4B&#10;hI+Mwv7zV7LDExEpdpS4pVCYSlVwLr4a57Z74QAXO28W4aBehFMnYzM3JTs8EZFiQ4lbCpVpcBDO&#10;LaMwl10HZctj//sC4aA+2C9n6/ExEZE4KHFLoTOOg3NcO5w7xmPanw2rVxKOH0l4/yDssl+SHZ6I&#10;SJGmxC1JY8qWw+l6Gc6QsdD0CPjua8KhfQlfnIjNWJfs8EREiiQlbkk6U6sOTt/BOFcPhOo1se/9&#10;l3BAL8KP38GGYbLDExEpUpS4pUgwxmCatcAZ+hDm7Itg00bsMw8S3nkj9n/fJzs8EZEiQ4lbihST&#10;lobToVt0//voNrD0R8KRNxM+cT929cpkhyciknRK3FIkmWr74PS8AefmkVC3AfbTmdHiJdNfxW7O&#10;SnZ4IiJJo8QtRZo5qAnOgNGYC3tDair25acIh/TFLpyX7NBERJJCiVuKPOOk4LQ5DWf4I5i2HeDP&#10;5YRjhpL94HDsn8uSHZ6ISKFKTXYAIvEy5Stiul+Fbd2ecNIE+HoO4aIvMaechenQDVOmbLJDFBFJ&#10;OLW4pdgxdRrg3DgCc+XNULEK9q2Xo/vfn3+o2ddEZK+nxC3FkjEGp8XxOHc8jOl4Lqxbi514H+Hd&#10;t2F/+SnZ4YmIJIwStxRrpnQZnM4X4Ax7CJofAz9+Szj8esLnHsauXZPs8ERECtxuE7fneUcURiAi&#10;+WFq1CKld3+cfkOh1n7YD98mHHAV4cw3sdnZyQ5PRKTAxNPifj7hUYgUENOkOc6gMRjvCrAh9oVH&#10;Ce+4DhssSHZoIiIFIp5R5d94ntcd+ATYuvKD7/txTWPleV5LYKTv+209zzsceANYHNs93vf9l/Yw&#10;ZpFcmdRUzCmdsS1bY199FjvrPcJ7b8ccdTym62WY6jWSHaKISJ7Fk7g7A92222aBlN2d6HneTcBF&#10;/H/CPxK4z/f9+/ckSJG8MJWqYi7ti21zGuGkx7BzP8F+MwdzeldM+y6YtFLJDlFEZI/tNnH7vl8m&#10;H+X/CJwNPBt7fSTQyPO8s4AfgGt931+fj/JFdss0aIRz693Yz2ZiX3ka+/oL2Fnv43hXwOEtMcYk&#10;O0QRkbjtNnF7nucA1wNNgWuAq4G7fd/f7Ygf3/eneJ5XP8emz4EJvu9/5Xlef2AIcFNeAhfZE8Zx&#10;MMedhD38GOybL2Lfn0r48J3Q5HCc83piatdNdogiInGJZ3DaPcBhQMvY8acBee3qfs33/a9i/54C&#10;HJ7HckTyxJQrj9PtcpzB46BJc/h2PuHQvoQvPo7NUOePiBR98dzjPgk4Apjn+/6/nuedCszP4/Wm&#10;e553te/7c2PlxrVSRHp6er72S/7tdXWcno49ogUbP/+IVRNGk/3e65i5H1Ppkj6UP7kTxknOFAd7&#10;XT0XQarjwqF6Tpx4EneW7/uh53kA+L6/yfO8zXm8Xi9gnOd5mcAK4Mp4Tlq2bNcLSaSnp+e6X/Jv&#10;r67jegdhB43BvPMa4bSXWDXmDla9Phnn/CsxB7iFGspeXc9FhOq4cKie8y+3Dz5md3M7e573JDAX&#10;+A/R6PLrgXK+719UgDHmxipxJ1dJqWO78m/sK09h53wEgDnuJEyXizGVqxbK9UtKPSeT6rhwqJ7z&#10;L5a4dzpyNp7+wGuJusr3BWYBFYDrCio4kaLCVNsHp+eNODfdCXUaYGe/H82+9s4U7OasZIcnIgLE&#10;9zjYGuCKQohFpEgwjZriDByN/Wg69rXnsS89if34HZxze2KaagZgEUmueB4HqwmMAU4BsoBpwA2+&#10;769OcGwiSWOcFMyJHbBHHR899/3h24RjhkCzo3HO7YGpUSvZIYpICRVPV/kE4CfgaOAEYBXwaCKD&#10;EikqTIVKOBdchTPwfmh0CHw9h3BQH8Ipz2E3bUx2eCJSAsUzqnx/3/c753h9o+d5WrFBShRTtwHO&#10;jXdG06a+9CR2mo+d/T6m22WYFido9jURKTTxtLiXeZ7XYMsLz/PqAMsTF5JI0WSMwWlxAs4dD2M6&#10;eLDuX+yEewnvuQ3765JkhyciJcQuW9ye500lWkykBjDf87z3gGygLfBN4YQnUvSY0mUwZ1+IbXUS&#10;4UtPwPzPCe/oh2nTHtP5AkyFSskOUUT2Yrl1lb+8i+1vJiIQkeLG1KxNSp/bsQu/JHxxAvaDt7Bf&#10;fII56wJM6/YYZ7cL6ImI7LFdJm7f95/O+drzvHKJD0ek+DFNj8A5eCx2xpvYqZOwzz+C/XA6zvk9&#10;MY2aJjs8EdnLxPM4WD9gBFA6tskQ53rcIiWFSU3DnHoWtmUb7JRnsLPeJ7ynfzRwreulmGo1kh2i&#10;iOwl4hmcdj1wDFAp9lUx9l1EtmMqV8W59Fqc2+6B/Q/CfvEx4cDehG/62KzMZIcnInuBeB4H+8H3&#10;fQ1GE9kD5gAX57Z7sJ/OwL7yNPa157CfvItz7hXQrKUeHxORPIsncT/oed6LwDtEM6cB4Pv+MwmL&#10;SmQvYBwH0+pkbPNjsW9Mxs54g/ChO+GQ5tH0qbXrJDtEESmG4kncfYgWGMk5OM0CStwicTDlymO8&#10;K7AnnEo4eQIs+opw6DWYkzphOp6HKatxnyISv3gSdz3f9w9KeCQiezlTuy7OdUPh688JX3wc+85r&#10;2M8+wHS5BHNs22SHJyLFRDyD0372PG/XK3qLSNyMMZjDj8EZ9hCm8wWwMQP71BjCkTezKViY7PBE&#10;pBiIp8W9AVjoed4XwKYtG33fPzNhUYns5UxaKUzHc7HHtcO+/BT2i4/58/pLMa1OwnS5GFOparJD&#10;FJEiKp7E/UrsS0QKmKlWA3PlTdg2p5Py8hNkzXof++WnmE7nY9qegUmN57+oiJQkxlqb7Bh2xy5b&#10;tmyXO9PT08ltv+Sf6rhw1N63Jr9Pfgr72nOQsQ5q18U5rwemSfNkh7bX0O9y4VA95196ejpEE57t&#10;IJ6Z09YSjSLfhu/7moRFpACZlFScth2wLY6Pnvv+aDrh/YPh8GNwvMsxNWolO0QRKQLi6YfLOdly&#10;KaAL0SphIpIApkIlzIW9sa3bE06aAPM/I1w4D9P+bMzpXTGlyyQ7RBFJot0mbt/3l263aZTneZ8D&#10;9yYmJBEBMPUa4tx8F3bOR9EAtjd97OwZmG6XYY46XrOviZRQ8TwOtg3P8w4mmpBFRBLMGIPTsg3O&#10;HQ9jOnSDtauxj91DeO/t2N+WJDs8EUmCPb3HbYi6y29OZFAisi1Tpizm7IuwrU4m9B+Hr+cQDuuH&#10;OfE0TOcLMOUrJjtEESkke3qP2wKrfd9fk6B4RCQXpmZtUq4egF04j3DyROzMadg5H2POuhDT+lSM&#10;o9V2RfZ2u+wq9zyvnud59YiS9ZYvgCqx7SKSJKbpkThDxmK6XgbZm7HPjyccfj128aJkhyYiCZZb&#10;i3sRUbLOOQLGAmWJEr4+2oskkUlNw7Q/G9uyDfbVZ7CfziC85zbM0a0xXS/DVK2e7BBFJAF2mbh9&#10;39/mppnneQboD9wY+xKRIsBUqYa5/Dpsm9MIJz0WjUL/eg6mQzfMKZ0xaaWSHaKIFKC4RpV7nrcf&#10;MAM4G2jp+/7jCY1KRPaYaXgwTv97MZdcA6VKY6c8Szj4auzXc9h+hkQ9SiZSfMUzqrwL8BjwFHCb&#10;7/tZiQ5KRPLGOA7m+FOwRxyLnfoidsZUwgeHQ9MjSDnnUsr+u55SM2aQunAhm5s2JbN9ezY1bEiY&#10;ojtfIsXFLhO353llgTHAGcB5vu+/V2hRiUi+mHIVMOdegT3hFMLJE2Dhl2Qv+gr+t4KyPy4jPLgJ&#10;2S1aUPa55yi/fDmbDzuMzHbt2NCoETYtLdnhi0gucmtxfwnUJ0reh3med1jOnb7vj05kYCKSfya9&#10;Hk6/YZT670tk+Y+z7oB9yahfk3L1m1J5yBCcWBd6qWnTKDtqFGkjRpB5zDFsPOAAJXCRIiq3e9yf&#10;Ay8CtYBDt/tqmst5IlKEGGMo98sf1PpoEZUW/06Ylsq63xbx1zGN2FS53P8fZy3lbr+d0h99RIWp&#10;UzFZuismUhTlNqr80kKMQ0QSxBhD6sKFOKGlYoZD6j4uG+Z/wob0avx53MGU/+0fKge/k5K5GWMt&#10;zq+/UnrCBDa7LhsOOSTZ4YvIdvZ4rvI95XleS8/zZm63rbvnebMTfW0RAWstm5tGnWRhrVqU+n0F&#10;+8xfQo3PAtLWbmB93X1Y3uYQ1u5fE2vA+fVXbM2alJo5czcli0gyJDRxe553EzABKJ1jW3Pg8kRe&#10;V0S2ldmuHdYYnBUryK4XTXxYZuU69p31HVUW/QLA6iZ1WXF8EzbWrILzxx+kLlyox8ZEiqBEt7h/&#10;JHr2GwDP86oDw4FrE3xdEclhY6NGrBs7FrN8OWG9ethYQjYWKi79i9ofLKT8L3+xuUIZ/l35P1bW&#10;KsOmRg13eP5bRJJvt4nb87wvPc/r4Xleud0duz3f96cAm2PlOMBE4HpgPdtOpSoiCWTT0ljXqROr&#10;p08nu1w5NgwZsjV5A6RkZVN10a9UaXQsaRtDNtSqyr+LPyV8/QXspk1JjFxEtmd294na87zjgP8A&#10;pwKvAON93497JQPP8+oDk4C+wJPAX0TznTcGnvB9//rdFKGP/CIFKAxDstavJ2vuXFLeeIOUhQsJ&#10;69YlrFuXUi+/jLNoEf/2v56MnxcSrvqblBr7UuWKfpQ9/iR1nYsUrp3+h9tt4t7C87wqQHfgBmAZ&#10;MNb3/ZfiOK8+MNn3/WO32zbJ9/3j4ri0XbZs2S53pqenk9t+yT/VceFIRj2bzZsp8+uvpH34IWmf&#10;fRbNpta2LRsbNSLM3oyd9hL23ddg82ZwD8U5ryemzv6FGmNB0u9y4VA95196ejrsInHHsx73lqR9&#10;EXAF8C/gAxd7ntfJ9/2L4yhCrWaRIsimprKhQQM2NGiAueyybe5pm7Q0TJeLscefTPji4/DNF4TD&#10;rsOceDqmc3dM+Yq5lCwiiRJPV/nzQAfgDeBh3/c/jW1PBf70fb9agmNUizvJVMeFo6jXs10wl3Dy&#10;RPhzGVSoiDn7Iszxp2Ccnc9zbozJdXDbzvbv7pz8Kup1vLdQPedfflvci4DrfN//K+dG3/c3e57X&#10;Kv/hiUhxYA49CqdxM+z7U6MFTJ59GPvh2zjnX4k5sAkAWVmWxYvXMmPG7yxcuJKmTavRrt1+NGpU&#10;kbQ0s9P9p55ah6yskJkzl+30HBHZVlz3uD3P6wC0B7KBqb7vF+bMDGpxJ5nquHAUp3q2q1diX30a&#10;+2n0p8C0bEN250uY+nEGfft+Qs4/K8bA2LHHc/rpdXjrrd+22d+0aTU6dqzPqFFf7fScTp3qFmjy&#10;Lk51XJypnvMvtxZ3PI+DDQbuI7q3nQE86nle34IMUESKF1OlGs7l/XBuvRvqH4j9/EMY3IvvHniM&#10;NJO9zbHWQt++n7Bgweodknq3bg13SNo5z1m8eG0hvBuR4iWeCVguAo7xfX+Q7/sDgJZAr8SGJSLF&#10;gWl4ME7/ezAXX82mMJVb3W9494S3aFdj29aWtTBz5jJq1/7/6SDS08vxyy/rdkja257zeyLDFymW&#10;4knc/wA5P/auBtYlJhwRKW6Mk0JK6/YMCHvw+JJG1C27nqdafMSTR31Ig/Jrth63ePFq9t33/xN3&#10;rVpR4s7NwoWr9Oy4yHbiGZw2F3jd87xHiWZBuxD4xfO8LgC+77+awPhEpBiw1tLw0HSGvnkEk35t&#10;yNAm8zip5nJO2OcPHl/SiLE/HkKjRlX45pu/t56zYkUGzZvXyLXcpk2ratpVke3E0+JuAlQgmnjl&#10;FmA/oBpwDXB14kITkeKkXbv9MAYWr6vM+XPacuW8VvyxsQy9Gn7Ph23e5Jw6S1ixfP3W45cty6Be&#10;vQrsqkFtDLRtu18hRS9SfOzJzGmpgPF9PyuxIe1Ao8qTTHVcOIp7PWdlWaZO/XWbAWilnc1c1fB7&#10;rnMDUsIsVlZpwEVvHsSCf6PpH3IbVT5u3Al07FhHo8qLIdVz/uXrOW7P82oCTwPtgFTP8z4ELvR9&#10;Xz8VEdkqLc3QqVNdXLcjM2f+zsKFq2jatCpt256Fqb4BXnuSavNm80arn/mu2lE8vfoY9j+0Dqec&#10;Uoe2bdP54INlOc7Rc9wiuxLPPe4Hgc+A84EUosVCxgOdExiXiBRDaWmGQw6pxCGHVNpuFrRKcNWt&#10;2O++Jpw8gSbLvmBU2W8xjbtjGh6ESU2ladPKCZ85TWRvEE/ibuT7vpfj9WDP8+JeHUxESqadJWDT&#10;uBnOoDHYD97C/vd57OQJ2I+mR4uXNG6mpC0Sh3gGp6V5nldmy4vYutz63yUieWJSUnBO6ogz/BFM&#10;6/aw/FfC0QPJHj8S+/cfyQ5PpMiLp8U9GXjP87wnY68vA15OXEgiUhKYipUxF/XBtm5POOkx+HI2&#10;4YK5mNO6YNqfgyldOtkhihRJu21x+75/B/A4cCpwGvAUMDSxYYlISWHqH4hzyyjMFf2gXAXs1MmE&#10;g3pj581W17nITuTa4vY8Lw0o7fv+k8CTnucdCnzv+77+N4lIgTHGYI5piz28JfbNl7Dvvk74yEg4&#10;+LDo/vd+9ZMdokiRscsWt+d5dYiW9OyYY/MAYIHneemJDkxESh5TphzOOZfgDH0QDj0Kvv+GcNi1&#10;hJMnYNdrpmURyL2r/B7gCd/3J2/Z4Pv+ucBzwN2JDkxESi6zbzopfQfhXDMQ9tkX+/5UwgFXEX40&#10;HRtm774Akb1Ybom7qe/7I3ey/U7giATFIyKylTmsBc6QBzHnXAJZWdhnHyIccSP2x++SHZpI0uSW&#10;uDN3ttH3/RDYmJhwRES2ZdLScE47B2f4w5hjToRf/kc46hbCx0djV/+T7PBECl1uiXuN53kNtt/o&#10;eV5DolXCREQKjalSHeeK63FuGQn1GmI/+4BwQG/Ct1/BZhX2EgoiyZPbqPL7gKme5/UFZhMl+WOA&#10;MUTd5SIihc4c2ATn9nuxn7yHnfIs9pWnsR+/i3NeD8yhRyU7PJGE22WL2/f9N4gS9ERgPbAWeAi4&#10;0/f9SYUTnojIjoyTgtO6fTT72kmd4O8VhGOHkT12GPYPrX8ke7dcn+P2ff8F4AXP86oBoe/7qwsn&#10;LBGR3TPlK2DO64k94dRo9rUFcwm/nY85pTPmDA9TpmyyQxQpcPFMeYrv+ysTHYiISF6Z/erj3DA8&#10;mjbVfwL79ivYz2ZizrkU07INxmh5UNl7xLPIiIhIkWeMwRzZCmfYw5hO58H6ddjHRxOOugW79H/J&#10;Dk+kwChxi8hexZQujXNmd5xhD8ERx8H/vicccT3hsw+R/e+qZIcnkm+77Sr3PK/edpsskOH7vh6g&#10;FJEiy+yzLym9bsV+9zXhpMewH01n+bzZ0Ol8zImnY1JSkh2iSJ7E0+KeBSwBvgHmAz8DyzzP+93z&#10;vOMSGJuISL6Zxs1wBo3BnNsDsNjJjxHecR32+2+SHZpInsSTuN8DLvN9v4rv+9UAj2hpz47A/QmM&#10;TUSkQJjUVJyTz6T2Y69iTjgVlv1CeN8AwkdGYf/5M9nhieyReBJ3M9/3n9nywvf9V4Ajfd//CiiV&#10;sMhERApYSpVqOBdfjdP/XjjAxc6bRTioN+HUydjMTckOTyQu8STuVM/zmm55Eft3iud5ZYC0hEUm&#10;IpIgZv+DcG4Zhbm8H5Qtj/3vC4SD+mC/nI21NtnhieQqnue4bwU+8DxvEVGiPwjoDgwFpiQwNhGR&#10;hDGOgzm2LbZ5S+wbPva9/xKOHwmNm+Gc2xOz3/bjckWKht22uH3fnwY0IrqfPRJo7Pv+DGC47/sD&#10;ExyfiEhCmTLlcLpeijNkHDQ9Er77mnBYX8IXJ2Iz1iU7PJEdxPM4mAP0ADrEjn/H87w7fd9fm+jg&#10;REQKi6m1H07fQfDNXMIXJ2Df+y/28w8xZ1+EaXUSxtHjY1I0xNNVfhfQDHiAqIV+JXAP0C+eC3ie&#10;1xIY6ft+W8/zmgCPxnb9APSIre8tIpJ0xhho1gKnyeHY917Hvuljn3kQ++HbOOdfiWl4cLJDFIlr&#10;cNppQCff91/zff9VoDNwejyFe553EzABKB3bNAK41ff9EwADdNrzkEVEEsukpeGc3hXnjvGYlm1g&#10;6Y+EI28mfOJ+7Got3SDJFU/idnzf37pKve/7m4B4V63/ETg7x+suvu/P8jyvFFAL+DfuSEVECpmp&#10;Wh2nxw04N4+Eug2wn84kHNCLcPqr2M3x/hkUKVjxdJXP9zzvfuDB2Os+RLOo7Zbv+1M8z6uf47WN&#10;TaH6HrAa+HoP4xURKXTmoCY4A0ZjP34X+9qz2Jefwn78Ls65PTCHHpns8KSEiSdx9wHGArOJuren&#10;A9fk9YK+7/8CNPI87wqikeqX7u6c9PT0fO2X/FMdFw7Vc+Llq47Pv5zsjuew5rlHWTftZcKxQylz&#10;9AlU6Xk9ael1Cy7IvYB+lxNnt4nb9/01bJdcPc87BNjjGz2e570O3OD7/o/AWiA7nvOWLVu2y33p&#10;6em57pf8Ux0XDtVz4hVYHXe+EOfIVoSTJ7Jxzses+PJTzClnYTp0w5Qpm//yizn9Ludfbh984mlx&#10;78ynQKU8nDcSeMrzvE1ABtFjZiIixY6p0wDnhuEwbxbhS09g33oZ++kMTNfLMEe3jkaoiyRAXhN3&#10;3L+Rvu8vBY6L/ftT4Pg8XlNEpEgxxsBRx+Mc2gL79ivR18T7sB+8hXN+T0y9hskOUfZC8Ywq3xlN&#10;5isiEmNKl8bp3B1n2EPQ/Bj48VvC4dcTPvswdu2aZIcne5m8Jm4REdmOqVGLlN79cfoNhVp1sB+9&#10;TTjgP4Qz3sBmxzWkR2S3dtlV7nneWnbesjZAuYRFJCJSzJkmzXEGjcF+8Cb2v5Owkx7DfjQ9mn3N&#10;PTTZ4Ukxl9s97qa57BMRkVyY1FTMyZ2xR7fBTnkWO+s9wntvxxx1fDSArXqNZIcoxdQuE3dsUJmI&#10;iOSDqVQFc8k12NanEU56FDv3E+w3czCnd8WcejamVOndFyKSg+5xi4gUAtPgIJxb78Zcdh2UKYd9&#10;/QXCQX2wX36KtRrvK/FT4hYRKSTGcXCOa4cz/BHMqWfD6n8Ix99F+MBg7PJfkx2eFBNK3CIihcyU&#10;LYfT7TKcwePgkObw7XzCoX0JX3wcm7E+2eFJEafELSKSJKZ2HZxrh+BcPQCq1cC+9zrhgKsIP3kX&#10;G4bJDk+KKCVuEZEkMsZgmh2NM/RBzNkXwaaN2KfHEd51E/anINnhSRGkxC0iUgSYtFI4Hbrh3DEe&#10;c3Rr+PkHwrtuInxyDPbfVckOT4oQJW4RkSLEVNsHp+eNODfdBXUaYGe/H3WfvzMFuzkr2eFJEaDE&#10;LSJSBJlGh+AMHI25oBekpGJfepJwaF/swi+THZokmRK3iEgRZZwUnBNPxxnxCKZtB/hjOeGYIWQ/&#10;OBz75/JkhydJktdlPUVEpJCY8hUx3a/Ctm5POGkCfD2HcNGX0cxrHbphSpdJdohSiNTiFhEpJkyd&#10;Bjg3jsBceRNUrIKd9hLhgF6Ecz7S7GsliBK3iEgxYozBaXECzh0PY87wYN0a7IR7Ce+5DfvrkmSH&#10;J4VAiVtEpBgypcvgnHUhzrCH4PBj4IdvCe/oR/j8eOy6NckOTxJIiVtEpBgzNWqR0qc/znVDYd90&#10;7AdvEd5+FeHMadgwO9nhSQIocYuI7AXMIc1xBo/FdLscwmzsC48Q3nE9dvHCZIcmBUyJW0RkL2FS&#10;U3FOPStafazVSfDbEsJ7+hM+dg925V/JDk8KiBK3iMhexlSuinPptTj974UGjbBffEw4sDfhmz42&#10;KzPZ4Uk+KXGLiOylTINGOLfejbn0WihdBvvac4SD+mDnf6bHx4oxJW4Rkb2YcRycVidF3eenngWr&#10;/iZ86E7CB4Zgl/+W7PAkD5S4RURKAFOuPE63y3EGj4MmzeHbrwiHXkPoP47NWJ/s8GQPKHGLiJQg&#10;pnYdnOuG4PTpD1X3wb77OuHAXoSz3seGYbLDkzgocYuIlDDGGMzhx+AMewhz1oWwcQP2qTGEI2/G&#10;Llmc7PBkN5S4RURKKJNWCucML5o+tcUJsGQx4Z03Ej41BrtmVbLDk11Q4hYRKeFMtRo4V96Ec9Od&#10;UGd/7Kz3o8VL3nkNu3lzssOT7Shxi4jI/7V37/FRVHcfxz9nAgSRgBWLsii2YkEx1jv6gHItFhBr&#10;8XKoN3yqUhEsVooFBUFAqrSKCgoq1XoXf2rRB1pRK6DipU9VbEnRAooXSFEUQQSNgZnnj9nwhJhw&#10;S3Y3E77vf9yd2Zn55bzU754zs+cA4NoUEoy6GXfOQHAB0WP3EI4dQvSvhbkuTcpRcIuIyBYuL4+g&#10;a2+CCXfguvSCj4sJbxnD5tsnEK1elevyBAW3iIhUwjVuQnDupQSjJsEP2sFbfyMcPZjwyQeJSr7O&#10;dXm7NQW3iIhUybU6iODK63EDhkHjJkR/tnj61L+/pNnXckTBLSIi2+ScI2jfieC6abjeHtavJbrr&#10;94Q3Xk300fJcl7fbqZfpC3jvjwduMLOu3vsjgcnAJqAE6G9mWrJGRCQBXH5DXN/ziDp2J3zsnnj4&#10;fPwVuM49cT89F7dnQa5L3C1ktMftvb8SmA7kpzfdAgw2s27ATGBEJq8vIiI1zzVvQd7gkQSXj4F9&#10;WxDN/wvhyIGE858mCjfnurw6L9ND5cuAvuXe9zOzRenX9YCvMnx9ERHJEFd4DMGYybizfg6bNxE9&#10;NI1w/FBKivTzsUzKaHCb2UziYfGy9x8DeO87AIOBmzN5fRERySxXrz7ByX3j1cc6dIcVy/lk+ADC&#10;6XV5DM4AABDTSURBVDcSrfk01+XVSS7TTwV67w8EHjGzDun3/YCrgNPM7IMdOIUeWxQRSYiSd4pY&#10;e+fv+GbJYlx+Q5r0u5CCvufiGuRv/2CpyFW2MeMPp5XnvT8P+AXQxczW7uhxxcXFVe5LpVLb3C/V&#10;pzbODrVz5qmNs6DJ3rS46V5WPvEg0RP3se7+qax7+k8E/iI4oj3OVZpFUkEqlapyX9Z+Dua9D4Bb&#10;gcbATO/9XO/9mGxdX0REssMFAUHHH8XD5z86DdasJrx9AuHksUSrVuS6vMTLeI87PRzeIf22Waav&#10;JyIitYNrtCeu30VEJ/UgnDEdit4kfPuXuO4/wfXph9ujUa5LTCRNwCIiIhnlUq0IrhhHMOhq2KsZ&#10;0bMzCUcNJHzleaIwzHV5iaPgFhGRjHPO4Y46gWDc7bjTzoWvNxL98VbCG35DtHxprstLFAW3iIhk&#10;jWuQT9CnH8G4abhjT4TlSwivH0Z43xSiL3b4meXdmoJbRESyzjX7LsElvyEYNgFSrYgWPBcPn//1&#10;KaJNm7Z/gt2YgltERHLGtT2c4JpbcOdcAi4gevRuwnGXEy1+K9el1VoKbhERySmXl0fQ9ZT452Od&#10;e8KqFYQ3j2bz1N8SrV6V6/JqHQW3iIjUCq6gCcF5gwhGTYKD28HC1whHDyZ86iGikpJcl1drKLhF&#10;RKRWca1aE/zmetzFv4bGBUSzHyUcfSnR6wvI9DTdSaDgFhGRWsc5R3B8Z4Lx03C9zoQv1hLe+TvC&#10;m0YRrXg/1+XllIJbRERqLddwD4LT+xOMvQ2OaA//XkQ47leED99JtGF9rsvLCQW3iIjUeq55irzL&#10;RhEMGQPNWxDN+3P887EX5hCFm3NdXlYpuEVEJDHc4ccQXDuZ4MyfQ+kmogenEk74NdGyxVWuPFbX&#10;ViTL6rKeIiIiu6q0NGLJkvXMnbuSoqLmtG87lNPdizRZ/BLhxBG8RjvePvSnHP/jdhx0UGPee+/L&#10;9GfXUFi4N926taRNmwLq1092kCu4RUSk1istjZg16yOGDFlA2YPl77+/Nxv79OG5V/MZ2+4N2jdd&#10;zGGLljDlyXZ8/+L+3PfQexQVrQFg9uwPmDhxIZMnn8ippx6Q6PDWULmIiNR6S5as3yq0Ac46qzUT&#10;Jy7kjc/34dSXT+bKfx7HV5vzGNH2nxw/51qu6F4C/P8BUQRDhixgyZJkP9Sm4BYRkVpv7tyVW4V2&#10;KtWIDz/8csu2CMejK1rT5YVT+MPyNuy/xwZ6LL2bGSe+zPf3/GLLcVEE8+atzHL1NUvBLSIitZpz&#10;bsuQd5n99ouDu6IvNjVg3NtH8+MFPVkctqJDkxU8d9Icrm77Fo3rlQJQVPR5oh9YU3CLiEitFkUR&#10;hYV7b7Vt1aqNtGrVuMpjln7ZlMdSFzJieTdWfb0HA1u/w/xOf+b01HIKD2ua6BnYFNwiIlLrdevW&#10;kvKd5OLiOLir6jg7Bwe0KuDht5vT/cVe3LSkkCb1S7nlyL9xwep7iN5fmp3CM0DBLSIitV6bNgVM&#10;nnziVkH92GPvMnz4Ud8Kb+dg4sT/4vHH3wWgJKzHrcsK6fZib1budxSN/rOU8LfDCO+/jeiLtVn8&#10;K2qGfg4mIiK1Xv36jlNPPYC2bfswb95Kioo+p7DwO/TosT9du6aYP794y7auXVty0EGNOfLIZlt9&#10;tmvXlrRoU0Dw7iLCGdOJXnqW6PWXcT85G9elN65eMiLRJWCcPyouLq5yZyqVYlv7pfrUxtmhds48&#10;tXF2ZKOdnXPfuk9d2baqtkebNxO98DTRUw/Bxg2QakXwswG4Q4/IaN07KpVKAVR6I0BD5SIikjiV&#10;BXRVHdFKwzwvj6BbH4Lr7sB16gn/+Yhw0jVsnnYD0acf13i9NUnBLSIiuy1X0JTg/EEEIydB60Pg&#10;zVcIRw8m/J+HiUpKcl1epRTcIiKy23MHtiYYPhF30VBo1Jho1gzC0YOI3ni51v10TMEtIiJCfC88&#10;OKELwXVTcb3OgHWfE94xkfCmUUQrP8h1eVsouEVERMpxDRsRnH4Bwdjb4IfHwb8XEY67nPCRu4g2&#10;fHu2tmxTcIuIiFTC7Zsi75fXEAwZDfvsRzR3NuGogYQvPkMUbs5ZXQpuERGRbXCHH0tw7RTcGRdA&#10;aSnRA7cTThhGtOztnNSj4BYREdkOV78+Qc8z4vvfJ3SFD98lnDic8O5JRGs/y2otCm4REZEd5PZq&#10;RnDRFQTDJ0Kr1kSvzSccdSnh008QlZZmpQYFt4iIyE5yBx9KMPJGXP/LoH4Doj/dR3jtL4kWvZ7x&#10;ayu4RUREdoEL8ghOOjmefa37qfDpKsLJ49g8eRzRx5mb8jUZM6qLiIjUUm7PxrifDSA66WTCGdNh&#10;0euEi9/C9TgNd8pZuIaNavR6Ge9xe++P997Pq7Btkvf+F5m+toiISLa4lgcSDB1PMHAENP0O0Zwn&#10;CEcNInxtXo3OvpbRHrf3/krgfODL9Pt9gPuBHwDvZPLaIiIi2eacg2M6EBQeQ/TMn4jmPEF0981E&#10;858mOPsS3IGtq32NTPe4lwF9y71vDIwBHsjwdUVERHLG5ecT/ORsgvFT4egO8O47hBOGEj5wO9H6&#10;ddU6d0aD28xmApvKvX/fzP5OFWuMioiI1CWuWXPyLh1BMHQ8tDiA6MVn4tnXnp9NtHnXZl9LxMNp&#10;6QXFd3m/VJ/aODvUzpmnNs4OtXMFqRRR5x58+ZfHWffgHUQz7qLeq8+z1yXDaHjEcTt1qmwFd7V6&#10;2MXFVT9Wn0qltrlfqk9tnB1q58xTG2eH2nkbju2Ea3sEzHyA0gXPsfrqS+N74mddiGvWfMvHtvXF&#10;J1u/4674OF3tWtxUREQkS1xBU4L+lxGMvAlaHwJvvEI4ehDhrBlE35Rs//jatkB4JSL1uHNLbZwd&#10;aufMUxtnh9p5x0VRRPS3+USP3wfr1kCz5gT+Qlr2OROqGK3WzGkiIiI54pwjOKFrvHjJj0+HtWsI&#10;p92wzWMS8XCaiIhIXeYaNsKd+d9EJ/Yg+ott87MKbhERkVrC7dcSd+EV2/yMhspFREQSRMEtIiKS&#10;IApuERGRBFFwi4iIJIiCW0REJEEU3CIiIgmi4BYREUkQBbeIiEiCKLhFREQSRMEtIiKSIApuERGR&#10;BFFwi4iIJIiCW0REJEEU3CIiIgmi4BYREUkQBbeIiEiCKLhFREQSRMEtIiKSIApuERGRBFFwi4iI&#10;JIiCW0REJEEU3CIiIgmi4BYREUkQBbeIiEiCKLhFREQSRMEtIiKSIApuERGRBFFwi4iIJIiCW0RE&#10;JEEU3CIiIgmi4BYREUmQepm+gPf+eOAGM+vqvW8N3AuEQJGZDc709UVEROqSjPa4vfdXAtOB/PSm&#10;ScDVZtYZCLz3p2Xy+iIiInVNpofKlwF9y70/xsxeSr9+GvhRhq8vIiJSp2Q0uM1sJrCp3CZX7vV6&#10;oGkmry8iIlLXZPwedwVhudcFwNodOSiVSlVrv1Sf2jg71M6ZpzbODrVz5mQ7uN/03ncysxeBXsDc&#10;HTjGbf8jIiIiu4dsB/cwYLr3vj7wNvB4lq8vIiKSaC6KolzXICIiIjtIE7CIiIgkiIJbREQkQRTc&#10;IiIiCZLth9NqRIVpVL9LPDvbXkAe0N/Mlue0wDqgQhsfCUwDSoElZnZxbqtLNu99PeAe4HtAA2AC&#10;sBhNB1yjqmjnD4EpxPNLlBD//2J1rmpMusra2MxmpfedA1xmZh1yV2HdlLgedyXTqP4OeNDMugDX&#10;AIfkqLQ6o5I2Hg1ca2adgIbe+1NyVlzdcB7wabo9ewK3oemAM6Gydr4FGGxm3YCZwIgc1lcXlG/j&#10;XsRtjPf+KODCXBZWlyUuuPn2NKodgf29988B5wDzc1FUHVOxjRcC+3jvHfHEOaU5qaruMOIvmRCP&#10;Em0CjtZ0wDWuYjuXAv3MbFF6Wz3gq1wUVoeUb+MAKPXe7w1cB1yes6rquMQFdyXTqH4PWGNmPYCP&#10;0DfoaqukjZcCk4F/Ac3Rl6NqMbONZrbBe18APAaMRNMB17jK2tnMPgHw3ncABgM357LGpKukja8B&#10;7gaGAhvQBFoZkbjgrsRnwKz061nAMTmspa66FehoZu2AB4iHdaUavPcHEM8ceJ+ZzWAXpwOWbavQ&#10;zo+mt/UDpgK9zeyzXNZXF5RvY+LRuoOJn4l5BDjUe6//X9SwRD6cVsFLQG/gIaATca9QatZnxL1A&#10;gGJAD5tUg/d+X+AZ4nut89KbF+7CdMCyDZW1s/f+POAXQBcz05ejaqri3+XD0/sOBB4xs6G5qq+u&#10;qgvBPQz4g/f+UmAd8X1uqVkDgEe996XAN+n3suuuIv4VxDXe+9FARHw/cIqmA65RFds5DzgM+ACY&#10;6b2PgBfMbGwOa0y6yv5d7mVmJbktq27TlKciIiIJUhfucYuIiOw2FNwiIiIJouAWERFJEAW3iIhI&#10;gii4RUREEkTBLSIikiB14XfcIonivQ+AXwFnE/+2uAEwGxhtZt/swvn+CCwysx2aocp73x24kfg3&#10;ty3SNaxI776eeEKjHT7fTtbaGbjNzA7fyeNCYB8zW1Nh+6+BQjP7eQ2WKVKrKbhFsu8O4rnIu5nZ&#10;eu/9HsDDxCuyXZDpi5vZ88BRAN77MUAzMxtStt973zvDJezK5BHbOkaTUchuRcEtkkXe++8R97T3&#10;M7MNAGb2lff+EqBDOsRXAu3NbFn6mGeJ15Cem/5nR+KVrp40s1EVzn8o8dKVexP3pCeb2b27UGpH&#10;7/0ZwL5AEXB2us6vgaeAHwLnAhuJ57Lf6nre+z2BPxLPWx0Cb5jZJelzF3jvHyFegjcfGGBmL3vv&#10;mwC3A0emj5kDXGVmIenFKtLrP08hXj3tY+ATNK+77GZ0j1sku44G/lUW2mXM7BMze9LMvgLuJT2t&#10;rPe+NdCGeCh9PJBvZm2Je8wdvfedys7hvc8jXqFpuJkdB3QBrvTet9+FOlNAt/S19wdOT29vADxl&#10;ZocC/yCemrWy6/UFGpvZ0UD7dH0Hpc/RErjJzI4C7gKuTW+fQry28+HAscARxFMalzeY+MvAIcDJ&#10;QKtd+NtEEk3BLZJdIdv/724acH46iAcA080sAroTL5mImZWaWdf0oiRl2gCtgXu89wuBF4CGpIfF&#10;d9KTZlaS7u0WES/nWmbBDlxvAXCY934e8VK7t5jZe+nj3jWz19Ov3yp37p7AbWV/H/EthV7pfWXD&#10;4d2Bh81ss5ltJF5cSGS3oqFykez6X+KlDvcs3+v23rcE7gTOMLOl3vt/Aj8lHo4+Nv2xTZS7n+u9&#10;3594qLpMHvB5updb9pnm7NpQcmm51xFbr6v85fauZ2bfeO8PJu6FdwOe995fRrzSXFXnrviFJgDq&#10;V9hWsZZNiOxm1OMWySIzKybuJd7jvS8AKHdvd3W5VZWmAr8HXjOzj9Pb/gpc4L133vt84mHqTuVO&#10;/2/ga+/9uenzHkDcW87UGvVVXs97PxC418yeM7OriJd+LEwf5yo9W3p5yPS58omX33y2wjFzgP7e&#10;+3zvfUOgXw3/TSK1noJbJPsGES/d+Yr3/k3gVeLAK79c6mygMfGweZmxxL3VfwBvALPN7Mmynenh&#10;5dOAi733/yAOuZFm9upO1lfxKe2ostfbud79QOC9X+y9/ztQQPwQW2XnLzME2Nd7vyj9N74D/LbC&#10;MXcS/+1FwDzgvYonEanrtKynSC3kve8A3Lmzv3cWkbpP97hFahnv/b1AZ+D8HJciIrWQetwiIiIJ&#10;onvcIiIiCaLgFhERSRAFt4iISIIouEVERBJEwS0iIpIgCm4REZEE+T/ut5NePjo8gAAAAABJRU5E&#10;rkJggg==&#10;">
</div>
+
</div>
<div class="clear"></div>
+
<div class="clear"></div>
  
  
</p><p class="c0"><span><b>pSB1C3 absolute quantification run #3</b></span></p><p class="c0"><span>Lysate from 100,000 stationary phase cells harboring K909006-pSB1C3 was compared against a 3-point standard of 10</span><span class="c1">5</span><span>, 10</span><span class="c1">6</span><span>, and 10</span><span class="c1">7</span><span> copies.</span></p><p class="c0 c2"><span></span></p><p class="c0">
+
</p><p class="c0"><span><b>pSB1C3 absolute quantification run #3</b>Lysate from 100,000 stationary phase cells harboring K909006-pSB1C3 was compared against a 3-point standard of 105, 106, and 107 copies.  Linear regression indicates approximately 30.9 copies of the target sequence for every cell in the reaction, or around 30 plasmid copies per cell.<p class="c0">
<div class="img-block">
+
<div class="img-block">
<!-- fig3 -->
+
<!-- fig3 -->
<img src="https://static.igem.org/mediawiki/2016/9/9c/T--genspace--pSB1C3_Absolute_Quantification_3.png" alt="">
+
<img src="https://static.igem.org/mediawiki/2016/9/9c/T--genspace--pSB1C3_Absolute_Quantification_3.png" alt="">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAfMAAAGMCAYAAADOe0tfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz&#10;AAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xm8TfX+x/HXd51zzLNIJ1HqnpWcktykKBlzZWhcSTTd&#10;q1xJt8GtpFBSrlQkQ7q3SdIqSeRqMKRyJdJAWRpcDZpuSnRwOOv7+2NtfocM27H32Wd4Px8PD2ev&#10;vfZ3fda3k8/+ftdnfZex1iIiIiLFl5PqAEREROTgKJmLiIgUc0rmIiIixZySuYiISDGnZC4iIlLM&#10;KZmLiIgUc0rmIiIixVx6qgMQKUyu654BLAAmBEHQN9/2y4D7giColYRjtgLmA5WCIMiJY//jgZpB&#10;ECw4iGNWAW4GLgCOAL4DZgHDgyD4rqDtFiCOQ4D2QRA8E3s9H3g3CIK/u65rgMeAC4EfgCHAyCAI&#10;aifguLv0oeu6IdA5CILZB9v2Ho5VEXgQ6AaUAf4NXF+Y/SyikbmUNpcAq4HuruuW3e29ZK6gdCBt&#10;zwCOK+iBYgn0HaAV0BdwgStify91XffogrZdAP8Azs33+lxgaOznU4FLY9taAFM5iPPeze59WAd4&#10;LUFt724C0BT4E3AaUBvwk3QskT3SyFxKDdd1yxCNVP8GTATOB6akNKg9Mwf5+QeBX4BWQRDkxbZ9&#10;5bruQmAO8E/gzIM8Rrx2OZcgCH7J97I6YIMgeDXftq1JOu4PCWp3T3KAa4IgWAbguu6DwHTXdU0Q&#10;BFpiUwqF0XKuUlq4rnse8CxwKPAUUDYIgnax9y4DRgIPADfGPvIkcFMQBKHrumlESfICoCqwDLgh&#10;CIJ3Y58/GriPaDQcAi/E3t8Um2afB1QGagFrgOwgCD7Od+z7giCoFZuGbkU0kn8jCII2ruseCjwE&#10;dAQ2AS8DNwZB8OsezrE60ZT6uXuaUnZdtzmwCGgUBMEnruuuIZraHhd7v37++FzXrR3rk/ax8/4K&#10;uDsIgsdi+88H3gBOBDoA/wOGBEHwL9d1BwODY4e2QRCk7ZhmB1YSTbETO9ehwFryXepwXfcEYBTQ&#10;HFgPjA+C4N7YeycD9wCnEA1KPgD6B0GwZC99uHOa3XXdDGAgcBlwGLA01p9L9nFOQ4Mg+Ofu/bmH&#10;/j0MmET0u9V+f/uLJIqm2aU0uQR4OwiC9UTJ9sxY8trhEKJ/vM+M7dsD+HvsvWuBLkBXounb1cBz&#10;AK7rVgPeIhpVtiCaNm5JNALekz19g96x7Tzga6Jkc15s23QgjyhxdQYaEE1J70lTouT2nz29GQTB&#10;YmAL0XTw3uSP7ymifmkNNCSavh7vum7+2oK/A7OJ+mU6MC72/n1E080ziaa585sK9Iodq05s353H&#10;dl23JjCXqC/+CFwF3OK67uWu61aKHe894HiiftlENNsCe+7D/MYCVwJ/JUrYK4HXYl+a9nZOD+92&#10;zr/juu5Y4JtYPNfta1+RRFMyl1LBdd2qQCdgWmzTi0Qj6Mvz7bYd6BEEwYogCF4BhhFdcwY4kigJ&#10;fhUEwX+BG4DLYkVcPYn+X7o0CIJPgiB4M9buhXu5Pr3XafQgCH4mStwbgyD4xXXd1kA20CvW9ntE&#10;SbCj67oN99DEIbG/N+7tGESj3EP28X7++GYCVwdBsDIIgi+A4URFXln59pkfBMEjsX4ZFHu/cRAE&#10;vwGbga1BEPy423luJboUQBAEP+6hMLA7kAv0DiKvECXfTUAFYARwSxAE/w2C4ENgPFE//a4P8zca&#10;+z24EvhbEASvBEEQxNr9Cui3v3PaR58BjAFOJhrVz419IREpFErmUlpcRPQP8nSAIAh+IvpH97J8&#10;+3wTBMG3+V4vAw6PVYaPByoRXXt+E7ga+Dh2TbQh8H4QBLn5PvsuUTJqdJBxHwdUBH52XXej67ob&#10;gYDoi8ixe9j/p9jfdffRZlViiTQO44HmruuOcV13DvAx0eg5Ld8+n+74IQiCHV8iMuJsf28aAh8G&#10;QbA9X9vPBEHwfOz696PANa7rPhqrBXiC+P49y4rttzhfu5bYpYd8+x3wOQVBsDp23bwn0ezIRXHE&#10;I5IQKoCT0uKS2N9rXNfdsc0AxnXdtrHXebt9Zkdy2BYEQeC67lHAWURVy/2Bfq7rnkI0Yt8Tw65J&#10;D/Y8xb6v/w/Tgf8C7fj9iP77Pey/lGiGoVnsc7twXbcp0ZeDd/cST3q+fQ3wCpBJNC0+j2hKOtjt&#10;M7n83sEW8eXurY3YdeklwCqi28CmEtUiTI6j3S17addh1/9WcZ2T67rliGZ8Xg2CYBNAEARbXNf9&#10;gn3PfogklEbmUuK5rluP6Br2YKKp0h1/mhJN214Z27Vu7Pr3DqcBa4Mg2Oy6bk/goiAIZgVBcA3R&#10;bV61Y+1+Apy4261uzYgS4ye7hbMjSVTOt233qfj8CfYTomS6KQiCL2JT3XlExXi/ux87NsXsA4Nj&#10;hV64rtvCdd0PXdftDNwFLItN1++IZ/dYdhy/CdAG+FMQBHcGQfAiUQU6xJ+sC1phuxrIjhUeEjuP&#10;O1zXfRa4mOgLVvsgCO4PguB1onvp4znuZ8A2fl8zcCrRrENBTCGqp9gRZxWiGYAVBWxP5IBpZC6l&#10;QU+ia7djdq8Ad133CeAvRCPVdOAZ13VvJkpqtxItvAJQBbjTdd2fiP7R70yU0N4D1gF3AE+6rnsn&#10;UBMYB7wWBMGqWGHVjuT3PdH12Rtd172F6EvF5bvFuwloGCu4ei12vGdd172JaHp9LNGU/3/3cr5/&#10;I7qEMN913aHA58DbwEtESS5/InsXuDQ2hV6OKNnvSITfEasjcF33aaIvMKNj7+9+j/7ebAIaua5b&#10;PwiCtXF+BuBpokVkxrmuOwo4JnZe1xF9ATnUdd2ziRJma+A2iG4/jF3u2NmH+a/Xx76YPQTc77ru&#10;b0SV+9cB9Ymq0A9IbBQ+CbjXdd1viS5z3Btr98UDbU+koDQyl9KgBzB1T7dyESXGMkSV6B8TJbeF&#10;RNeK7wuCYBJA7NatsbHtq4iqqy8IguDzIAg2E1XBVyWa/n2OaJW58/Mdx8basUTJuyHRlPV1RF8a&#10;8htN9AVkTmz/rkRJYl7szzqg097uYY7VA5wai2EsUcLrTHSr3QvA1NgoHaIk+A1R9fvjRLMXYayd&#10;dbHz7E00Q/Ag8DDwIdGsxt7kj+txotu/VsZuc4tL7Dr1n4jqAt6PHXdoEARPEc08TCK6te2DWHx/&#10;iR13R1w7+3APMd1KdIviY0R1EQ2BM2OzHrvvu6dz2t2NRFP9k4muvW8Gzg6CIIzzdEUOWtLvM/c8&#10;7xTgXt/3W3uedxLRP4ZbgPd939ftGyKFzHXdDkTT1PNTHYuIJEZSR+ae5w0gtoBCbNNEoL/v+62A&#10;DZ7n9Ujm8UXk94IgeFWJXKRkSfY0+2fsui5zXd/334n9vIioeEhEREQOQlKTue/704kKaHb43PO8&#10;02M/dyG6RUZEREQOQmFXs18JjPY8Lx14k73fn5ufFo8XEZHSKO71Ggo7mZ8N9PB9/2fP88YQrX28&#10;X+vWrUtoEJmZmQlvs7RTnyae+jTx1KeJpz5NvMzMzAP+TGHfmvYpMM/zvLeADb7vz9nfB0RERGTf&#10;kj4y931/LbFFKnzfnwXMSvYxRUREShMtGiMiIlLMKZmLiIgUc0rmIiIixZySuYiISDGnZC4iIlLM&#10;6RGoIiJSLLz//vvceeedHHnkkQD89ttvZGZmMmjQINLS0nbuZ61l/PjxrFmzhtzcXMqXL891113H&#10;YYcdtt9j5Obmcvfdd/PLL79QoUIFbrnlFqpWrbrLPs888wzz5s2jYsWKXHTRRZx66qk73/vyyy/p&#10;27cv06dPJyMjg3fffZdJkyZRvnx5Tj75ZHr27JmYztiNRuYiIlJsNGnShPvvv5/777+fiRMnkpaW&#10;xttvv73LPkuWLOGnn35i5MiRjB49mi5dujBu3Li42p8xYwYNGjRg9OjRtG/fnqeeemqX99esWcO8&#10;efMYP348//jHP3jsscfIzc0FICcnh/Hjx1OmTBkg+lIxatQo7rzzTkaPHs2XX37JihUrEtALv6dk&#10;LiIixdK2bdtYv349lStX3mV7tWrVWL16NfPnz2fDhg20aNGCIUOGAPDGG2/Qu3dvBgwYwJAhQ3jl&#10;lVd2+exHH31Es2bNADjllFNYtmzZLu+vXbuWE088kfT0dMqUKUPdunX5/PPPARg1ahS9e/emXLly&#10;AGzYsIHKlStTp04dALKzs/noo48S3g+gaXYRESmA8LnHsMveZl1aGnl5eQlp0zRtgXPhFfvcZ/ny&#10;5dxwww2sX78ex3Ho0qULTZo02WUf13W58cYbmTlzJg899BC1a9emb9++NGrUiPHjx/Poo49SsWJF&#10;brnllt+1n5OTQ8WK0TPAKlSoQE5Ozi7vN2jQgClTprB582Zyc3NZuXIlXbp04YknnqB58+Y0aNAA&#10;a6NHilSrVo2tW7fy1VdfkZmZyTvvvMMxxxxzMF20V0rmIiJSbDRp0oTbb7+dX3/9lQEDBuwc9eb3&#10;xRdfcMQRR3D77bcDsHTpUoYMGcI///lPqlSpQqVKlQBo3Ljx7z5boUIFNm/eDESJfce+O9SrV49z&#10;zjmHm2++mdq1a9OwYUOqVq3Ka6+9Ru3atZk9ezbr169nwIABPPjgg9xyyy088MADlClThiOPPPJ3&#10;198TRclcREQOmHPhFXDhFSl70EqVKlUYOHAg119/PY8++ig1atTY+d6yZctYu3YtN954I8YY6tev&#10;T/ny5alevTpbtmzhl19+oVq1agRBwGmnnbZLu9nZ2SxevBjXdXnnnXc4/vjjd3l/w4YN5OTkMGbM&#10;GH777Tf+/ve/c9RRRzF58uSd+1x88cXcd999ALz77ruMHDmStLQ07rjjDv70pz8lpT+UzEVEpFiq&#10;X78+559/Pg899BCDBw/euf28885jwoQJ/OUvf6FSpUoYY7jtttsAuP766xk4cCAVK1Zk69atv2uz&#10;W7du3HPPPfTv35+MjAwGDRoEwHPPPUfdunU59dRT+fLLL/nrX/9KRkYGffr0wZhdn1RqjNk51X7I&#10;IYfQp08fypYtS7t27ahfv35S+sLsOGARZvUI1KJPfZp46tPEU58mXnHu00mTJlGvXj3OOuusVIey&#10;i3yPQI37eeaqZhcRESnmNM0uIiKlUu/evVMdQsJoZC4iIlLMKZmLiIgUc0rmIiIixZySuYiIJIW1&#10;kJOTx/btRf6uqWJPyVxERBIqL8+ycuWv3H33B3Tt+io9esznlVfW8b//5Sb8WNOnTz/oNq655hq+&#10;//77A/7cl19+yfXXX3/Qx08EVbOLiEhCLVz4A5ddNo+8vP8fkb/99ne0b1+Xf/zjFGrXLpuwY02e&#10;PJlzzz03Ye0dqN0XjEkVJXMREUmYr7/eTJ8+C3dJ5Du89trXLFp0FOecc0QB2/6aESNGkJ6eThiG&#10;nHTSSWzcuJHRo0fTu3dvRo4cyW+//cZPP/1Et27d6Nq1K9dffz3HHHMMa9asIScnhyFDhlC7dm0e&#10;ffRRli5dSq1atfj1118B+PHHH3nwwQfJzc1l/fr1XHnllbRo0YIrr7ySunXrkpGRwTXXXMOwYcMA&#10;qF69+s7YHn30Ud5//33CMOSMM86ge/fuBTrHglIyFxGRhFm9egObNm3b6/sPPfQR7dplUqlS2gG3&#10;vXTpUho2bMjVV1/NRx99RNWqVZk5cybXXXcdn376KW3btqVly5b89NNPXH/99XTt2hWAhg0bcs01&#10;1/DPf/6TuXPnctJJJ/HRRx8xYcIEcnJy6NWrFxBNm3ueR+PGjVm5ciWPP/44LVq0YPPmzVx22WUc&#10;ffTRjBkzhrZt23L22Wczf/58Zs6cCcC8efN44IEHqFGjxu8eq1oYlMxFRCRhNm7ceyIH+P77zWzZ&#10;klegZN6pUyeeeeYZ/v73v1OpUiX+/Oc/73yvevXqPP/88yxcuJAKFSqwffv2ne/teOxorVq1+Pnn&#10;n/n6669xXReInpJ21FFHAVCzZk2eeuopZs+eDbDLo12POCKaTfjqq6/o3LkzED2UZUcyHzhwII88&#10;8gg///zzzuehFyYVwImISMLUrl1+n++fcEJNKlUq2Djy7bff5oQTTmDUqFG0atWKZ555ZucDTXzf&#10;p1GjRgwcOJAzzzyT/M8d2f26dv369Vm1ahUAmzdvZu3atQD861//4qyzzuLWW2+lSZMme2zjyCOP&#10;ZMWKFQA729i+fTtvvPEGt99+O/fffz9z5szhhx9+KNA5FpRG5iIikjBZWVWoX78Sa9du2uP7ffs2&#10;oly5go0jXdfl3nvv5amnnsJau7MKffjw4XTq1IkxY8Ywf/58KlasSHp6Otu2bdtjgdoxxxxDs2bN&#10;6NOnDzVr1tx57fvMM89k/PjxTJkyhUMOOWTntfT8bfTs2ZO7776bBQsW7HyWenp6OpUrV6Zv376U&#10;K1eOk08+mdq1axfoHAtKT02ThFCfJp76NPHUp4m3pz4Ngo1ccslcvv02Z+c2Y2Dw4D9yySVHU6HC&#10;gU+xlyYFeWqaRuYiIpJQrluZWbP+xCef/MKqVT9TvXo5TjyxJg0aVKRMGV3dTQYlcxERSbg6dcpS&#10;p86htG59aKpDKRWSnsw9zzsFuNf3/dae550IjAe2Aat93/9Lso8vIiJS0iV1vsPzvAHAJGDHcj93&#10;AEN83z8DKOd53tnJPL6IiEhpkOyLF58B+dfZWw4c4nmeASoTjdBFRETkICQ1mfu+Px3Ynm/Tp8AY&#10;YCVQG1iQzOOLiEjqGGtJz8nB2b59/zvLQSnsArjRQAvf91d5ntcXuB/ot78P5SvTT5hktFnaqU8T&#10;T32aeOrTxNu9T/Nyc9n6n/+Q9txzpM+bR1ijBtuvvhqnZUvKHHlkgR9Okpuby4wZM7jwwgvj/szS&#10;pUupUqUKWVlZBTpmcVHYyfwnYGPs53XAafF8SPeZF33q08RTnyae+jTx9tSnlebPp/Jll2Fiy6Gm&#10;ARlvv01u+/b89I9/kFvABVW+++47pkyZQosWLeL+zFNPPUXr1q2pVKlSgY6ZCgX5wlnYybw38Kzn&#10;eduA3NhrEREpIcp+/TWV+/TZmcjzK/Paa5RdtIjcc84pUNuTJ09m7dq1PPHEE6xZs2bnCm3XXnst&#10;Rx11FCNGjGDdunXk5uZy3nnnUb9+fZYsWcKnn37KUUcdRa1atQ7q3IqypCdz3/fXEhuB+77/NtAy&#10;2ccUEZHUyFi9GrNpz0u5ApR/6CE2t2vH9gKMlHv27MmaNWvIzc3lpJNOomvXrnzzzTeMGDGCESNG&#10;8NFHH/Hwww8DsGzZMrKysmjWrBlt2rQp0YkctGiMiIgkkNm4cZ/vO99/j7NlCxzEtPcXX3zBe++9&#10;x4IFC7DWsnHjRsqXL88111zDqFGjyMnJoV27dgVuvzhSMhcRkYQJ93M9fPsJJ5BXwETuOA5hGFKv&#10;Xj3at29PmzZt+OWXX5g9ezbr169n9erV3HnnneTm5tK9e3c6dOiAMYYwDAt0vOJEyVxERBJmW1YW&#10;2+vXJz32WNHdbenbl7xy5QrUdrVq1cjLyyMnJ4cFCxYwc+ZMcnJyuPzyy6lRowbr16+nX79+pKWl&#10;cdFFF+E4Dg0bNmTSpEkcdthh1KtX72BOrUjTU9MkIdSniac+TTz1aeLtqU/LBwFVL7kE59tvd26z&#10;xpAzeDCbLrmEvAoVCjvMYkVPTRMRkZTb7LrkzZpFmU8+IW3VKmz16mw78US2NmhAWKZMqsMrkZTM&#10;RUQk4XLr1CG3Th1o3TrVoZQKerCsiIhIMadkLiIiUswpmYuIiBRzSuYiIiLFnJK5iIhIMadkLiIi&#10;UswpmYuIiBRzSuYiIiLFnJK5iIhIMadkLiIiUswpmYuIiBRzxSKZ5z08HPvt16kOQ0REpEgqHg9a&#10;eX8x4YdLMC07YLpejKlaPdURiYiIFBnFYmTu9B0ItQ/DLpxDeNvVhDOmYLfkpDosERGRIqFYJHPT&#10;pDnOkLGYXn2hXHnsrKmEA68mnD8bu317qsMTERFJqWKRzAFMWhrOGR1x7p6I6dYDcnOxUyYQDu6H&#10;XfY21tpUhygiIpISxSaZ72DKlsPp3B1n+ERM67Php+8JJ4wgvGcAdvWKVIcnIiJS6IpdMt/BVKmG&#10;0+NqnKEPY5q2gDWrCUcOJG/sMOy6L1MdnoiISKEpHtXs+2AOzcT0uRn7RUA47XH4YAnhh0sxLdtF&#10;le/VaqY6RBERkaQqtiPz3ZkGLs5Nw3H63Q6H1cW++WpU+T79KWzOb6kOT0REJGmK/cg8P2MMND4Z&#10;5/iTsIvmYWc8jZ39HHbhHEzn7phWHTHpGakOU0REJKFKzMg8P+Ok4bRsjzNsIubcXpCXh506ifCO&#10;awiXLMSGYapDFBERSZgSmcx3MGXL4nS6EOfuRzBtu8D6/2En3cf3N1yOXfXhnj9jTCFHKSIicnCS&#10;Ps3ued4pwL2+77f2PO8Z4FDAAEcC//F9v0eyYzCVq2C698a27YJ9cTLbliyEUYMguynO+ZfhHHo4&#10;5Vavpsy8eaSvWMH27Gxy27RhS1YWNkPT8iIiUrQlNZl7njcA6AVsAvB9/+LY9mrAPOBvyTz+7kyt&#10;OpjeN3FIj958P2EkrFhGuPI90jOPptLk6WRszgWg7KxZVBgxgk1jxrCpSxcldBERKdKSPc3+GXDu&#10;HrYPBR7yff+HJB9/j8r8oSHODXfhXDcYp+ah5H7zGd+f0Yhf3MMJ09MAMNZSqX9/yq1enYoQRURE&#10;4pbUZO77/nRgl8XTPc+rBbQBHk/msffHGIPJbkrVw7Kp8cEanNztbDy6Dt+emc3Go2pjHYOxljLz&#10;56cyTBERkf1Kxa1pFwBTfN+PezH1zMzMhAeRmZnJ9u3bsStXkvHNesp/+zOb6tfm12Pq8EvDI9hY&#10;vzZVV68jfcUKateuTXp6ibqLLymS8d+ptFOfJp76NPHUp6lXWBkqf4l4O+CuA/nwunXrEhpMZmbm&#10;zjarZmeTMWsWTmipsuZ7Kn79PzYeXYeN9Wuz/sSjSCuzEbvgFcxxTX7XjjFGD3iJyd+nkhjq08RT&#10;nyae+jTxCvLlqLCSef6MlwV8UUjH3a/cNm2oMGIEJpaU07blUW3VN1Ra+yMbsjLJOdzAA4PhuBOj&#10;yvfD6qnyXUREihRTDEaWNpkjc7NtG5VmzqRS//47EzqANYZNDz3ExsaNyJvxNHy8HICMzAbUfPol&#10;MjZv3XXfUl75rm/niac+TTz1aeKpTxMv38g87oVPSv2FYJuRwaYuXdjuupSZP///R9utW7MlKwsy&#10;Mki7fij24+UweQLb1n3Bd2ccR6W1P1Ll829J25a3s/J9u+uyuVGjVJ+SiIiUMqU+mUOU0Dc3asTm&#10;Ro32eh3cHNeEKnUaYV5bxIasTDY1OJTfjqhJlc+/o9J/f8AJo8p3JXMRESlsSua72dtlB2MMGStX&#10;Unbdeip89zOb6tfi16MPY8OxddkUq3xP++gjFcWJiEihK9FrsyeStZbt2dkAmNBSec0PHLZgBZU/&#10;/46wTDrrGx/J+jIbCT9cqmQuIiKFSsn8AOS2aYPN9yAWZ3se1YJvqPPGCip8/RN5W34jHDOUcNQg&#10;7H8/TWGkIiJSmiiZH4AtWVlsGjNml4QOkLZ1O2Wuuom020bB8X+E4CPCu28kfGQk9sfvUhStiIiU&#10;FrpmfgDiqnzvfwd21YeEzz+OffdN7Hv/wZz5J8zZF2EqV0n1KYiISAmkZH6A4qp8P/YEnIH3YZe9&#10;jZ3+FHbuTOyiuZizzsO064YpWzYFkYuISEmlafaDsK9CN+M4OCefjnPnw5juvSEtHfviZMJBVxO+&#10;+So2L68QIxURkZJMyTzJTHoGTtsuOHdPxHS6EHI2YZ8cSzi0P/aDd1X5LiIiB03JvJCYChVxzu2F&#10;M2wi5vQO8N03hGPvIrxvIPaLINXhiYhIMaZkXshM9Zo4l/bDGTIGGjeD1SsJ7xlA3oR7sd9rfWMR&#10;ETlwKoBLEZNZj7R+g7CrVxI+/xgsW0T4/juYM87CdO6OqVIt1SGKiEgxoZF5ipmsRji3jsTpczPU&#10;PBQ7fzbhwKsJZ07Fbtmc6vBERKQYUDIvAowxmKYtcIaOxfToA2XKYF+aQjioD+Ebc1T5LiIi+6Rk&#10;XoSY9HSc1p1whk/EdO4OWzZjJ48jHHItdvliVb6LiMgeKZkXQaZcBZxuPaLb2Vp1hB/WEY4bTjji&#10;Zuxnn6Q6PBERKWKUzIswU7U6Ts++OEPHQpPm8PkqwhE3kzduOPa7r1MdnoiIFBGqZi8GTJ26pPUd&#10;iP3sE8Jpj8PyxYQfLMG07IDpejGmavVUhygiIimkkXkxYo5piPP3e3H6DoTah2EXziG87WrCGVOw&#10;W3JSHZ6IiKSIknkxY4zBNGmOM2QspmdfKFceO2tqdDvb/NnY7dtTHaKIiBQyJfNiyqSl4bTqGBXJ&#10;desBubnYKRMIB/eLntamyncRkVJDybyYM2XL4XTuHt3O1roT/PQ94YQRhPcMwK5ekerwRESkECiZ&#10;lxCmSjWcHn1whj6MadoC1qwmHDmQvLHDsOu+THV4IiKSRKpmTyBjTMqnt82hmZg+N2O/CKLK9w+W&#10;EH64FNOyXVT5Xq1mSuPbl4L2X1HodxGRVFIyP0jbtllWr97IvHnfsGLFerKza9CmzeFkZVUmI8Ok&#10;LC7TwMW5aTh8uJRw2uPYN1/FvrMA064b5qzzMBUqpiy2/Araf0W130VEUsEUgxGNXbcusY8GzczM&#10;JBFtbttmmTnzK/r3f4v83WgMjBnTki5djigSicXm5WEXzcW+NAV+WQ+VKkdPZmvVEZOekZBjFKRP&#10;C9p/xaXfD1aifk/l/6lPE099mniZmZk7foz7HzJdMz8Iq1dv/F1CAbAW+vd/i9WrN6YmsN2YtDSc&#10;0zvgDJuIObcX5OVhp04ivOMawiULsWGYkrgK2n/Fpd9FRAqLkvlBmDfvm98llB2shfnzvyncgPbD&#10;lC2L0+lCnLsfwbTtAuv/h510H+Hwm7CrPiz0eAraf8Wt30VEki3p18w9zzsFuNf3/dae59UCJgHV&#10;gDTgUt/31yQ7hmQwxrBixfp97rNixc9FsjjLVK6C6d4b27YL9sXJ2CULCUcNguymOOdfhql7ZPJj&#10;KGD/FedSAcQ6AAAgAElEQVR+FxFJlqSOzD3PG0CUvMvGNv0DmOz7/pnA7cCxyTx+Mllryc6usc99&#10;srOrF+mEYmrVwel9E85to+DYE2DFMsI7ryN8bDR2/Y9JPXZB+68k9LuISKIle5r9M+DcfK9bAHU9&#10;z3sN6AEsSPLxk6pNm8MxeylPMAZatz68cAMqIHPkH3BuuAvnusGQWQ+7aC7hoL8SPv84NmdT0o5b&#10;0P4rKf0uIpIoSU3mvu9PB/IvFn4ksN73/fbAV8AtyTx+smVlVWbMmJa/SyzGwEMPnU5WVuXUBFYA&#10;xhhMdlOcOx7EXHEdVK6CfeUFwluvInz1Rey2bQk/ZkH7ryT1u4hIIhT2feY/ATNjP88EhhXy8RMq&#10;I8PQpcsRuG5n5s//hhUrfiY7uzqtWxff+52Nk4Y5rS32jy2x81/Gvvwc9rl/YefNwpxzCaZZK4yT&#10;mO+ABe2/ktjvIiIHo7CT+ZtAJ+Bp4AxgZTwfynfPXcIkss369aFt2yzCMMRxHJwEJbuUu6IfeRf0&#10;YuOzj7Fx5rPYfz5A+oLZVLviWso1af673QvapwXtvxLb7/kk43e/tFOfJp76NPUKO5nfBDzqed5f&#10;gQ1E1833q6guGlNqdPJwmrXCzniabe+8wY+D+sFxJ0aV7/WOBtSnyaA+TTz1aeKpTxOvIF+OtAKc&#10;HBD75ReE056Aj5cDYJqfiTmnJ4cff6L6NMH0e5p46tPEU58mXkFWgNPa7HJATL0GpF0/FPvx8qja&#10;ffEC7NK3+LnLRdhWnTAVVXwmIlLYSt5FRikU5rgmOIMewPz5Bqhag03TnyYceBXhnGnY3K2pDk9E&#10;pFRRMpcCM46D0/xMnLvGU+0vfwMMdtoThLf/lfDtudgwL9UhioiUCkrmctBMRgaVz+2Jc88jmI7n&#10;w8ZfsY+PJrzzb9iPlmk1NhGRJNtvMvc876TCCESKP1OhEs75l+EMG485rS2s+5JwzFDCUYOw//00&#10;1eGJiJRY8YzMn056FFKimBq1cK64DueO0XD8HyH4iPDuGwkfGYn98btUhyciUuLEU83+oed5PYC3&#10;gJ0Ldfu+v+9HV0mpZ+oeSVr/O7CrPowq3999E/vefzBn/glz9kWYylVSHaKISIkQTzLvBly42zZL&#10;9AhTkf0yx56AM/A+7LK3sdOfws6diV00F3PWeZh23TBly+6/ERER2av9JnPf98sVRiBSshnHwZx8&#10;OrZJc+wbc7Czno2epb5gNqZrD0yLthhH3w9FRApiv8nc8zwHuAHIBq4F+gH/8H1f9x3JATPpGZi2&#10;XbCntsG+8gL29RnYJ8diX5uBc/7lcMIfMXt7vqmIiOxRPAVwI4ETgFNi+3cEHkhmUFLymQoVcc7t&#10;hTNsIub0DvDdN4Rj7yK8byD2iyDV4YmIFCvxJPO2wOXAFt/3NwAdgPbJDEpKD1O9Js6l/XCGjIHG&#10;zWD1SsJ7BpA34V7s91rvWUQkHvEk822+74c7Xvi+vxXYnryQpDQymfVI6zcIZ8BwOCoLli0iHHwN&#10;4ZQJ2F9/SXV4IiJFWjzV7Cs8z7sGSPM8zyW6fv5+csOS0spkZePcOhLeW0T4wpPY+bOxi+ZjOp6L&#10;aX8OpqzqMUVEdhfPyPw64CTgUOBtoBLwt2QGJaWbMQbTtAXO0IcxPfpAmTLYGVMIb7ua8I052DzV&#10;XoqI5BfPrWm/An8uhFhEdmHS0zGtO2FPPRP7yovYV6djJ4/Dvv4SznmXwomnqPJdRIT4bk2rDYwm&#10;KnrbBswGbvR9XxcypVCYchUw3XpgW3XEzpyKfetVwnHD4ehjcS64AnNMw1SHKCKSUvFMs08CvgCa&#10;AacDPwMTkxmUyJ6YajVwevXFGToWmjSHz1cRjriZvHHDsd99nerwRERSJp4CuCN93++W7/VNnud9&#10;lKyARPbH1KlLWt+B2M8+Jnz+cVi+mPCDJZiWHTBdL8ZUrZ7qEEVEClU8I/N1nucdteOF53l1gW+T&#10;F5JIfMwxx+HcPAKn70CofRh24ZyoSG7GFOyWnFSHJyJSaPY6Mvc8bybRA1VqAe97nvc6kAe0Bj4s&#10;nPBE9s0YA02a45xwMvat17Azn8HOmop949+YLhdjTu+ASY9nAkpEpPja179yz+9l+8vJCETkYJi0&#10;NEyrjtjmZ2JfexE7Zzp2yoRY5XsvOOk0Vb6LSIm112Tu+/4T+V97nlch+eGIHBxTthymc3fsGR2j&#10;EfrCVwgnjICjsnAuuByTlZ3qEEVEEi6eW9OuB+4Gdjx02qDnmUsRZ6pUw/Tog23bNXqG+rK3CUcO&#10;hMbNcM67FJNZL9UhiogkTDwXE28AmgOfJzkWkYQzh2Zi+tyM/SIgnPY4fLCE8MOlmJbtosr3ajVT&#10;HaKIyEGLJ5l/6vu+Ct6kWDMNXJybhsOHSwmnPY5981XsOwsw7bphzjoPU6FiqkMUESmweJL5WM/z&#10;ngVeJVoBDgDf959MWlQiSWCMgcYn42SfhF00F/vSFOzs57AL52A6d8e06ohJz0h1mCIiByyeZH4N&#10;0UNW8hfAWUDJXIolk5aGOb0Dtlkr7NyXsHOmYadOws6diTmnJ+aPLTFOPEswiIgUDfEk83q+7/8h&#10;6ZGIFDJTtiym04XY08/CvvwsdsG/sZPuw776YlT5fuwJqQ5RRCQu8Qw//ut5XmbSIxFJEVO5Ck73&#10;3jh3jcM0OwPWfkY4ahB5o4div/5vqsMTEdmveEbmm4EVnue9C2zdsdH3/a7xHMDzvFOAe33fb+15&#10;3onALGB17O3xvu8/d4AxiySFqVUH0/smbPtuhNOegBXLCFe+hzm1DaZbD0yNWqkOUURkj+JJ5tNi&#10;fw6Y53kDgF7AptimpsAo3/cfKEh7IoXBHPkHnBvugpXvET7/eFQs9+6bmDadMZ0uwFSolOoQRUR2&#10;sd9kvvtKcAfoM+Bc4KnY66ZAlud55wCfAtf5vv/bQbQvkhTGGMhuinPcidjFC7Aznsa+8gL2zVcx&#10;Z3uY1mdjMlT5LiJFQzwrwG0kql7fhe/7Vfb3Wd/3p3ueVz/fpneASb7vL/c8byAwBBgQf7gihcs4&#10;aZjT2mL/2BI7/2Xsy89hn/sXdt4szDmXYJq1UuW7iKRcPNPs+RezLgOcR/T0tIJ40ff9DbGfpwNj&#10;4vlQZmbi6++S0WZpV+L79Ip+5F3Qi43PPsbGmc9i//kA6QtmU+2KaynXpHlSDlni+zQF1KeJpz5N&#10;vXim2dfutmmE53nvAPcV4HiveJ7Xz/f9pUBbYFk8H1q3bl0BDrV3mZmZCW+ztCtVfdrJw2nWCjvj&#10;aba98wY/DuoHx52Ic/5lmHpHJ+wwpapPC4n6NPHUp4lXkC9HB/ygZ8/zjiVaRKYg/go85HleLvAd&#10;cFUB2xFJKXPIoZg/3/D/le8fv0/48fuY5mdGC8/UrJ3qEEWkFDnQa+aGaKr97/EeIDayPy3283Kg&#10;5YGHKVI0mXpHk3b9ndiPl0eV74sXYJe+FRXIne1hKlZOdYgiUgoc6DVzC/zi+/6vSYpHpFgyxzXB&#10;GdQYu2Qh9sXJ2NdmYN9+HfOnC6Jb2sqU3X8jIiIFtNcyXM/z6nmeV48oge/4A1Attl1E8jGOg9P8&#10;zGgluQuvBAx22hOEt/+VcNFcbFjQulERkX3b18h8JVECN/m2WaA80ZeAtCTGJVJsmYwymA7nYFu2&#10;w/57Gvb1l7CPjY7WfD//csg+KbqPXUQkQfaazH3f3+Vin+d5BhgI3BT7IyL7YCpUwpx/GbZ1J+yM&#10;Kdj/zCMcMxSOPSF6kEv9Y1IdooiUEHFVs3uedzgwGagMnOL7/ur9fEREYkyNWpgrrsO270o47clo&#10;zfdhN2BOPh1zbi9MrTqpDlFEirn9Ll3led55wAdE94SfqkQuUjCm7lGkXTcY58ZhUP8Y7LtvEt7e&#10;l3DqJOxG1ZSKSMHtdWTueV55YDRwNtDd9/3XCy0qkRLMHHsCzsD7sMvexr7wJHbuTOyiuZizzsO0&#10;64Ypq8p3ETkw+5pmfw+oT5TQT/A874T8b/q+f38yAxMpyYzjYE4+HdukOfaNOdhZz0a3tC2Yjena&#10;A9OibapDFJFiZF/J/B1gMVAn9ie/3z14RUQOnEnPwLTtgj21TfRUttdnYJ8ci31tBpuvugF7eANV&#10;vovIfhlri3xetlqbvehTnyaG/fkn7MxnsG+9DjaErEY451+OaeCmOrQSQb+niac+Tbx8a7PH/U1e&#10;z24UKUJM9Zo4l/bDGTKGcs1Oh9UrCe8ZQN6Ee7Hf6x9MEdkzJXORIshk1qPW4AdwBgyHo7Jg2SLC&#10;wdcQTpmA/fWXVIcnIkWMkrlIEWaysnFuHYnT52aoWRs7fzbhwKsJZ03Fbt2S6vBEpIiI56lp7wHj&#10;gCm+7+ckPyQRyc8YA01b4DQ+Bfvmq9E19RlTsAv+jelyMaZle0yaVlcWKc3iGZn3A04HPvc8b6zn&#10;eY2SHJOI7IFJT8dp3Qln+ERM5+6wOQc7eRzhkGuxyxdTDIpZRSRJ4q5m9zyvGtADuBFYB4zxff+5&#10;JMa2g6rZiwH1aeLtr0/tL+uxM6di33oVwhCOPhbngiswxzQsxCiLF/2eJp76NPGSVs0eS+S9gKuA&#10;DYAPXOp53pMHGKOIJIipVgOnV1+coWOhSXP4fBXhiJvJGzcc+93XqQ5PRApRPNfMnwY6AbOAv/q+&#10;/5/Y9vHAD8kNT0T2x9SpS1rfgdjPPiZ8/nFYvpjwgyWYlh0wXS/GVK2e6hBFJMnieWraSuBvvu//&#10;mH+j7/vbPc9rkZywRORAmWOOw7l5BLz/DuELT2AXzsG+swDT/hzMWedgylVIdYgikiRxXTP3PK8T&#10;cBaQB8z0fX9+sgPLR9fMiwH1aeIdTJ/avDzsW69hZz4DG36GylWjyvfTO2DS43rycYmk39PEU58m&#10;XlKumXueNxgYRXStPAeY6Hle/4IEKCKFw6Sl4bTqiHP3REy3HpCbi50ygXBwv+hpbap8FylR4vmK&#10;3gto6vv+BgDP80YBi4AxyQxMRA6eKVsO07k79oyO2FlTsQtfIZwwAo7KwrngckxWdqpDFJEEiKea&#10;/SdgY77XvwCbkhOOiCSDqVINp0cfnKEPQ9PTYM1qwpEDyRs7DLvuy1SHJyIHKZ6R+VJghud5E4Ht&#10;QE/gS8/zzgPwff+FJMYnIglkDs0krc8t2C8CwmmPwwdLCD9cimnZLqp8r1Yz1SGKSAHEk8yPi/19&#10;427bryV6rrmSuUgxYxq4ODcNhw/fJZz2RLRM7DsLMO26Yc46D1OhYqpDFJEDsN9k7vt+awDP89IB&#10;4/v+tqRHJSJJZ4yBxs1wsptiF83FvjQFO/s57MI5mM7dMa06YtIzUh2miMQhnkVjagNPAG2AdM/z&#10;3gB6+r6vexFESgCTloY5vQO2WSvs6zOwr7yAnToJO3cm5pyemD+2xDh6wKJIURbP/6FjgcXAoUBt&#10;4E1gfDKDEpHCZ8qWxTnbw7n7EUzbLrD+f9hJ9xEOvwm76sNUhyci+xDPNfMs3/e9fK8He563MlkB&#10;iUhqmcpVMN17Y9t2wU5/Cvvum4SjBkF2U5zzL8PUPTLVIYrIbuIZmWd4nlduxwvP8yoQFb7FxfO8&#10;UzzPm7/bth6e5y2KP0wRKWymVh2cqwbg3DYK3ONhxTLCO68jfGw0dv2P+29ARApNPCPzqcDrnuc9&#10;Fnt9BfB8PI17njeAaNGZTfm2NQGuPMA4RSRFzJF/wLlxGKx4j3Da41Gx3LtvYtp0xnS6AFOhUqpD&#10;FCn19jsy933/LuCfQAegI/A4MDTO9j8Dzt3xwvO8msAw4LoDDVREUscYgzm+Kc4dD2KuuA4qVcG+&#10;8gLhrVcRvvoidptuchFJpX2OzD3PywDK+r7/GPCY53nHA6t8349rmt33/eme59WPteUAjwI3AFs5&#10;gAXkRaRoME4a5rS22D+2xM6bhZ39PPa5f2HnzYoq35udocp3kRTY61PTPM+rC8wD7vB9f2ps27NA&#10;Y6BNvLemxZL5M0B/4DHgR6A80BD4l+/7N+ynCT0RQqSIytu4gY3PPsbGmc/C9m1kHO1S7YprKdek&#10;eapDEykJ4h707iuZPwN84Pv+vbttHwQc6/t+z3gOEEvmU33fP3W3bc/4vn9aHE3oEajFgPo08YpT&#10;n9r/fY+d8TT2nTfAWjiuSVT5Xq9BqkPbRXHq0+JCfZp4BXkE6r6m2bN93794D9uHAysOIC7Q6Fqk&#10;0BljCu1Rp+aQQzF/vgHbvhvhtCfg4+WEn7yPOaVVNP1es3bS4ivM8xQpqvaVzHP3tNH3/dDzvC3x&#10;HsD3/bXAafvbJiIHb9s2y+rVG5k37xtWrFhPdnYN2rQ5nKysymRkJL9MxdQ7mrTr78R+vJzw+cex&#10;ixdgl74Vq3y/kO1lKiUkvlSfp0hRs69p9vnAlb7vr9lt+9FEU+TNCiE+0DR7saA+TbwD7dNt2ywz&#10;Z35F//5vkf9/a2NgzJiWdOlyRKEmOhuG2CULsS9Ohp9+wJavyMf12nHumAy25P3/OOJA4zuY89Tv&#10;aeKpTxMv0dPso4CZnuf1BxYR3cbWHBhNNNUuIkXI6tUbf5fgILqE3b//W7huZxo1qlJo8RjHwTQ/&#10;E9v0NOz82eS99CyNghnMP6MCo1Yfzwvf1CfEOeD4itp5ihQFe72HxPf9WURJ+1HgN2Aj8DAw3Pf9&#10;ZwonPBGJ17x53/wuwe1gLcyf/03hBhRjMsrgdDiHx44ZwLjPG1KzzBbub/wO/275CmfWWgfYA4qv&#10;qJ6nSCrt8z5z3/enAFM8z6sBhL7v/1I4YYnIgTDGsGLF+n3us2LFzykrFjPG8N4nm5kVNOaJtcdw&#10;Y9YKLjh8DU+evJC3/1eb4atOjCu+on6eIqkS1+oOvu+vVyIXKbqstWRn19jnPtnZ1VOW4PLH9+2W&#10;itz04Sl0fKsj8344jBaH/MDLLV/lb5X/TfjDt3G3szepPE+RVNFSTSIlRJs2h2P2Ui5jDLRufXjh&#10;BrSb3eNbtbEaly9txUWLW/PBLzX4wy8fEN7el3DqJOzGX+NuJ7+icJ4iqaBkLlJCZGVVZsyYlr9L&#10;dMbAQw+dTlZW5dQEFrO3+Bb/fChrLx5KeOVNUL0mdu5MwtuuInzZx27dGnc7ReU8RVJhr7em7eB5&#10;Xr3dNlkgx/f9n5IW1W7H061pRZ/6NPEK0qc77r+eP/8bVqz4mezs6rRuXXTuv95ffHb7Nuwbc7Cz&#10;noVNv0K1GpiuPTAt2mKctLjb2Rv9niae+jTxCnJrWjzJ/Csgk6iaPQSqAtuB/wEX+r6f7OeSK5kX&#10;A+rTxDvYPi3qRWD7is/m/IZ95QXs6zMgNxcOOwLn/MvhhD9idhuSH8h56vc08dSniVeQZB7PNPvr&#10;wBW+71fzfb8G4BE9BrUz8MABxigihaQoJ3LYd3ymQkWcc3vhDJuIOb0DfPcN4di7CO8biP0iiLsd&#10;kdIinmTe2Pf9J3e88H1/GtDU9/3lQJmkRSYipZ6pXhPn0n44Q8ZA42aweiXhPQPIm3Av9nuNBkV2&#10;iCeZp3uel73jReznNM/zygEZSYtMRCTGZNYjrd8gnAHD4agsWLaIcPA1hFMmYH/VXbMi+1w0JuYW&#10;YIHneSuJkv8fgB7AUGB6EmMTEdmFycrGuXUkvLeI8IUnsfNnYxfNx3Q8F9P+HEzZcqkOUSQl9jsy&#10;931/NpBFdH38XqCh7/vzgGG+79+e5PhERHZhjME0bYEz9GFMj6uhTBnsjCmEt11N+MYcbF5eqkMU&#10;KXT7Teae5znAX4C/AbcC13qel+77/sZkBycisjcmPR2n9dk4wydiOneHzTnYyeMIh1yLXb5YhXFS&#10;qsRzzfweoA3wIHA/0XPIRyYzKBGReJlyFXC69cC5eyLmjI7wwzrCccMJR9yM/eyTVIcnUijiuWbe&#10;Efij7/vbADzPexn4ALg+mYGJiBwIU60GpldfbLuuhNOfhOWLCUfcDE2a45x3KaZO3VSHKJI08YzM&#10;nR2JHMD3/a3Atn3sLyKSMuawuqT1HYhz871w9LFRUh/cj/CpceSt/1+qwxNJinhG5u97nvcAMDb2&#10;+hrgw+SFJCJy8Mwxx+HcPALef4fwhSewC+fw7ZI3oF03zFnnYMpVSHWIIgkTz8j8GqA6sAj4D1AL&#10;uDaZQYmIJIIxBtOkOc6QsZiefTHlK2BnTSUceDXh/NnY7dtTHaJIQux3ZO77/q/A5fm3eZ7XCFif&#10;pJhERBLKpKVhWnWkzjndWffUBOyc6dgpE7Cvv4RzXi846bTfrfkuUpwU9BGo/0loFCIihcApXwGn&#10;c/fodrbWneCn7wknjCC8ZwB29YpUhydSYAVN5voKKyLFlqlSDadHH5yhD0PT02DNasKRA8kbOwy7&#10;7stUhydywOIpgNsTrcYgIsWeOTSTtD63YL8ICKc9Dh8sIfxwKaZlO0zXizHVaqY6RJG4FHRkLiJS&#10;YpgGLs5Nw3H6DYI6h2PffDVaHnb6U9ic31Idnsh+7XVk7nneRvY8AjeA7ukQkRLFGAONm+FkN8Uu&#10;mot9aQp29nPYhXMwnbtjWnXEpOtBkVI07WuaPXsf74mIlEgmLQ1zegdss1bY12dgX3kBO3USdu5M&#10;zLm9ME1bYBxNakrRstdk7vv+2sIMRESkKDFly2LO9rBndMS+/Cx2wb+xj4zE1p+Oc8HlmGNPSHWI&#10;Ijvp66WIyD6YylVwuvfGuWsc5uTTYe1nhKMGkTd6KPbr/6Y6PBGg4NXscfM87xTgXt/3W3uedxww&#10;MfbWp8BffN8Pkx2DiMjBMrXqYK4agO1wDuHzj8OKZYQr38Oc2gbTrQemRq1UhyilWFJH5p7nDQAm&#10;AWVjm+4GbvF9/3SiQrouyTy+iEiimSP/gHPjMJz+gyGzHnbRXMJBfyWc9gQ2Z1Oqw5NSKtkj88+A&#10;c4GnYq/P833fep5XBqgDbEjy8UVEEs4YA8c3xWl0InbxAuyLT2PnTMO++Sqm04WY1mdjMlT5LoUn&#10;qSNz3/enA9vzvbae59UDVgA1iZ6LLiJSLBknDee0tjjDxmPOvwzCEPvcvwhv/yvh4gXYUFcRpXAY&#10;a5O7mJvnefWBZ3zfP2237X8GTvd9//L9NKHV5kSkWMjbuIGNzz7GxpnPwvZtZBztUu2KaynXpHmq&#10;Q5PiKe6l05NeAJef53kzgBt93/8M2AjkxfO5devWJTSOzMzMhLdZ2qlPE099mniF0qedPJxmrbAz&#10;nmbbO2/w46B+cFwTnPMvw9RrkNxjp4B+TxMvMzPzgD9TqMkcuBd43PO8rUAO8JdCPr6ISNKZQw7F&#10;/PkGbPtuhNOegI+XE37yPuaUVphzemJq1k51iFLCJH2aPQGsRuZFn/o08dSniZeqPrUfL49uZ/tq&#10;DaSnY9p0jgrlKlYu9FgSTb+niZdvZB73NLsWjRERSTJzXBOcQQ9g/nw9VK2BffVFwoFXEc6Zhs3d&#10;murwpARQMhcRKQTGcXCat45WkrvwSsBgpz0RVb4vmosN4yohEtkjJXMRkUJkMsrgdDgHZ/gjmLPO&#10;g183YB8bTXjn37AfLaMYXPqUIkjJXEQkBUzFSjgXXI5z9wTMaW1h3ZeEY4YS3n87du1nqQ5Pihkl&#10;cxGRFDI1auFccR3OHQ9CdlNY9SHhsBsIHxmJ/fG7VIcnxURh35omIiJ7YOoeRdp1g7GffBCt8/7u&#10;m9j3/oM580+Ysy/CVK6S6hClCNPIXESkCDENG+MMvA/T+yaoXhM7dybhbVcRvuxjt6ryXfZMyVxE&#10;pIgxjoPT7Iyo8r17b0hLw744mXDQ1YRvvqrKd/kdJXMRkSLKpGfgtO2Cc/cjmE4XQs4m7JNjCYf0&#10;x37wrirfZSclcxGRIs5UqIhzbi+cYRMxLdvDd98Qjr2L8L6B2C+CVIcnRYCSuYhIMWGq18S57Fqc&#10;wWOgcTNYvZLwngHkTbgX+72WVC3NVM0uIlLMmMPrkdZvEHb1imjN92WLCN9/B3PGWZjO3TFVqqU6&#10;RClkGpmLiBRTJisb59aROH1uhpq1sfNnEw68mnDWVOzWLakOTwqRkrmISDFmjME0bYEz9GFMj6uh&#10;TBnsjCmEt11N+MYcbJ4q30sDJXMRkRLApKfjtD4bZ/hETOfusDkHO3kc4ZBrscsXq/K9hFMyFxEp&#10;QUy5CjjdeuDcPRFzRkf4YR3huOGEI27GfvZJqsOTJFEyFxEpgUy1Gji9+uIMGQtNmsPnqwhH3Eze&#10;uOHY775OdXiSYKpmFxEpwcxhdUnrOxD72cdR5fvyxYQfLMG07IDpejGmavVUhygJoJG5iEgpYI45&#10;DufmETh9B0Ltw7AL50RFcjOmYLfkpDo8OUhK5iIipYQxBtOkOc6QsZiefaFceeysqdHtbPNnY7dv&#10;T3WIUkBK5iIipYxJS8Np1RFn2ARMtx6Qm4udMoFwcD/ssrdV+V4MKZmLiJRSplx5nM7do9vZWneC&#10;n74nnDCC8N6/Y1evTHV4cgCUzEVESjlTpRpOjz44Qx+GpqfBFwHhyFvJGzsMu+7LVIcncVA1u4j8&#10;X3t3HiZVdeZx/Htu00AiLZsCaQQXIkQFFQloQGQTRlDiwuTggsHEgBqMJAZGRcAQkYQhLqBRwURx&#10;iZpXecDIJIhRUIwS1oBAkBAMRBkRZURZxG7unT9u9UynbaSrqYXb/fv8Q9Wtuue89T7089a599Q5&#10;IgC45sUUXHsz0aa3CGfNhFVLCFcvw519bjzzvVHTfIcoB6CRuYiI/At3QjuCUZMIrh8LLVoSLZof&#10;z3yf/TjRnt35Dk8qoZG5iIh8jnMOTutC0L4T0esvEf3uSaLfP0P06gu4CwbjepyHq1OY7zAlRSNz&#10;ERE5IFdQQNC9H8HE6biLhkBpCdHTDxGOH0G4dBFRGOY7REHFXEREqsDVq0dwvieYNAPXZyDs+IBo&#10;xhS23XgV0frV+Q6v1lMxFxGRKnNFDQkuHUZw+/24zt0p+ds6wjvHsn/qBKJ3/pHv8GqtrN8z996f&#10;CfzczHp5708HpgGlwD7g22a2PdsxiIhIZrmjW+CGj+aoK4ax7YEpsGY54doVuG/0xl14Oa7J0fkO&#10;sQISPlQAABDqSURBVFbJ6sjcez8aeAiolzp0DzDCzHoDs4Gbs9m/iIhkV90TTyb48USCG26D4tZE&#10;r79EOPY6wlmPEu3Zle/wao1sX2bfCFxc7vlgM3sz9bgOsDfL/YuISJY553AdOhGMvwd31UhocCTR&#10;vFnxmu/z5xCVlOQ7xBovq8XczGYTX1Ive74NwHvfFRgB3J3N/kVEJHdcUEDQrQ/BxAdwg4ZCGBI9&#10;8zDhuOsIFy/UzPcsctleUN97fyzwlJl1TT0fDNwCXGhmm6vQhFb8FxFJoP0ff8TH9gi7njcoLaGw&#10;TTsafecH1O94Vr5DSwpX1TfmdNEY7/0QYDjQ08w+qup5W7duzWgcxcXFGW+ztlNOM085zTzlNPMO&#10;mtMBgwm69CR67jeULF7I9rHXw8kdCQYNxbU+IXeBJkhxcXHa5+SsmHvvA2AqsBmY7b2PgFfMbEKu&#10;YhARkdxzRzXHXX0jUd8LCWc9CutWEv71L7gze+AuGoJr2izfISZe1ot56lJ619RTrdIvIlJLudZt&#10;KPjRT4nWrSR8dibR4oVEy17D9b4AN+BbuCOK8h1iYmnRGBERySl3ckeCsXfjrv4RNGxCNH8O4Zjh&#10;hPNmEX22L9/hJZKKuYiI5JwLAoKzesUryX3ru4AjmvVoPPP99ZeIwv35DjFRVMxFRCRvXGFdgn4X&#10;xWu+/9sl8PFOokemEv70h0RvLifbv7iqKVTMRUQk79wRDQj+/SqCOx7Ede0DW7cQTptAeNc4os0b&#10;8x3eYU/FXEREDhuuydEE3xlJMP4eaN8J1q8mnHgj4YwpRNvfy3d4h62c/s5cRESkKtwxx1Mw8jai&#10;v66K13lfuohoxRu4nv1x5w/GFR2Z7xAPKxqZi4jIYcuddBrBmF/gho2Cxk2JXnqe8NbhhP9lRPs0&#10;872MirmIiBzWXBAQdDknnvl+6TAoKCCa8wTh2GsIF83XzHdUzEVEJCFcnUKCPgMJ7piBG/At2LOL&#10;6LH7CH9yA9GqpbV65ruKuYiIJIr78hEEF19JMHE67uy+8N67hPfdTviLMUSb3sp3eHmhYi4iIonk&#10;GjclGPoDgtumwWldYMNawp+NJnxwMtG2z2/+4lyVNyFLHM1mFxGRRCtt1opNfUeys/EKvvL6byle&#10;/idKl7/BzlN702DwEDZtr8PLL7/LmjU7aN++Cb17t6Rt2yIKC2tOcVcxFxGRxCopiVi48D3Wr/+I&#10;yZPfJYq6MaDFO9zUbhXHr/4jJWsXsfTD05j659bs3V+HuXM3M3nySqZNO5uBA1vVmIKuy+wiIpJY&#10;GzZ8wubNu5g8eSXx/DfH799rRZ9XBzB2bSd27oErGy1hUY+5XNFqIwUuJIrghhteY8OGT/Idfsao&#10;mIuISGItWfI+W7bsouJE9tIo4LHNJ9J94QW8WtSTosJSftZhGfO7z6Nf83eIoogFC97NT9BZoMvs&#10;IiKSSM453n9/L1u27Drge3bvL+SJnZ15+IPjOXffq1x6zCZ+1ek1lu44ilfeLMS5k2vET9o0MhcR&#10;kUSKoohmzb5E69YNvvB9rVsXsf6/HWPWdKbvov7Me68lnZt8wKjwCUp/eQfRe+/kKOLs0chcREQS&#10;q0uXZuzfH+Ecn7vUDuAcFBcfwdatewD4++4jGb6iO50bb+fxS7bw5ZWLCVctwXXvhxt4Ga5h4xx/&#10;gszQyFxERBKrbdsijj22ATfd1JGKPyN3DqZM+QbPPvv3zx0fevsl1B87heD7Y6DZV4hemUd46zWE&#10;zz1J9OmeHH6CzNDIXEREEquw0NGzZwtat25Au3aNWLZsO2+//TGnnNKEc89tSZs2RZx6alMWLHiX&#10;NWv+h/btG9OrV7nfmXc8i+DUzkSvvUj0/FNEc58meuUP8Si9ez9cnWSUSZeAG//R1q2fX8nnUBQX&#10;F5PpNms75TTzlNPMU04z73DLadkqb5XVNufcF052iz7dS/Tic0QvzIZ9e6FZMcElV8IZXXO6elxx&#10;cXHZwyp3qsvsIiJSY0RRdMCCfbDBq6v/JYKBlxJMehDXawB8uI3wwcmEP/8Pog1rsxFuxqiYi4iI&#10;lOOObExw+bUEE34JnbrCprcIp9zC/vsmEm3dku/wKpWMmwEiIiI55poXU3DtzUSb3iKcNRNWLSFc&#10;vQx39rm4b16Ga9Q03yH+H43MRUREvoA7oR3BqEkE14+FFi2JFs2PZ77Pfpxoz+58hwdoZC4iInJQ&#10;zjk4rQtB+05Er79E9LsniX7/DNGrL+AuGIzrcR6uTmHe4tPIXEREpIpcQQFB934EE6fjLhoCpSVE&#10;Tz9EOH4E4dJFRGGYl7hUzEVERNLk6tUjON8TTJqB6zMQdnxANGMK4aRRROtX5zweFXMREZFqckUN&#10;CS4dRnD7/bjO3WHzRsI7x7J/6gSid/6RsziyXsy992d67xdUOHaX9354tvsWERHJBXd0C4Lhowlu&#10;vRPadYA1ywl/OpLwkalEO7Znvf+sToDz3o8GrgR2pZ4fBTwGnAisz2bfIiIiueaOO5HgxxNhzQrC&#10;WTPjyXJLF+H6DMT1H4T78hfv8FZd2R6ZbwQuLve8AXAb8HiW+xUREckL5xyuQyeC8ffgrhoJDY4k&#10;mjeLcMw1hPPnEJWUZLzPrBZzM5sNlJZ7/g8zW0oa682KiIgkkQsKCLr1IZj4AG7QUAhDomceJhx3&#10;HeHihRmd+a4JcCIiIlnk6tYjOG8QwaTpuL4Xws4dRL++i/COG4nWrcxIH7laNOaQRuLldpDJmGy0&#10;Wdspp5mnnGaecpp5ymlVFUPbcZRedjU7H3+APQv+QHj3bdQ/4ywaXvUD6rZpV+2Wc1XMK25Vk9a+&#10;q9oC9fCnnGaecpp5ymnmKafVdPl1BGf3I5z1KJ+uWMynK/+MO7MH7qIhtOxwetrNaT9zyQjlNPOU&#10;08xTTjNPOT100bqVhM/OhH++DXXqUDTwUhp974eg/cxFRESSwZ3ckWDs3birfwQNm/DJ7CfSbkMb&#10;rYiIiOSZCwLcWb2IOnWj4Yb0l4PVyFxEROQw4Qrr0qDvN9M+T8VcREQk4VTMRUREEk7FXEREJOFU&#10;zEVERBJOxVxERCThVMxFREQSTsVcREQk4VTMRUREEk7FXEREJOFUzEVERBJOxVxERCThVMxFREQS&#10;TsVcREQk4VTMRUREEk7FXEREJOFUzEVERBJOxVxERCThVMxFREQSTsVcREQk4VTMRUREEk7FXERE&#10;JOFUzEVERBJOxVxERCThVMxFREQSTsVcREQk4VTMRUREEk7FXEREJOHqZLsD7/2ZwM/NrJf3vg0w&#10;EwiBNWY2Itv9i4iI1HRZHZl770cDDwH1UofuAsaYWQ8g8N5fmM3+RUREaoNsX2bfCFxc7nknM1uU&#10;evwH4Nws9y8iIlLjZbWYm9lsoLTcIVfu8SdAw2z2LyIiUhtk/Z55BWG5x0XAR1U5qbi4OOOBZKPN&#10;2k45zTzlNPOU08xTTvMv18V8hff+HDN7FegPvFyFc9zB3yIiIlJ75bqYjwIe8t4XAn8Fns1x/yIi&#10;IjWOi6Io3zGIiIjIIdCiMSIiIgmnYi4iIpJwKuYiIiIJl+sJcHlRYUnZo4lXpWsEFADfNrO38xpg&#10;AlXI6enAA0AJsMHMvpff6JLHe18HeBg4DqgL3AGsQ8sfV9sBcroFuJd4/Yt9xH//2/MVY9JUllMz&#10;ez712uXA9WbWNX8RJs8B/p8uJs06VeNH5pUsKfufwBNm1hMYB3wtT6ElViU5HQ/8xMzOAep778/P&#10;W3DJNQT4IJXD84D70PLHh6qynN4DjDCz3sBs4OY8xpdE5XPanzineO87At/NZ2AJVllO065TNb6Y&#10;8/klZbsBx3jvXwQuBxbmI6iEq5jTlcBR3ntHvBhQSV6iSjYj/qOF+Jt4KXCGlj8+JBVzWgIMNrM3&#10;U8fqAHvzEViClc9pAJR475sAE4GReYsq2SrmtBToCrRKp07V+GJeyZKyxwE7zKwv8E/0zTxtleT0&#10;b8A0YC3QDH1BSpuZ7TGz3d77IuAZ4Fa0/PEhqSynZvY+gPe+KzACuDufMSZNJTkdB/wauBHYjRb5&#10;StsB/vaPBz5Mp07V+GJeiQ+B51OPnwc65TGWmmIq0M3MTgYeJ748LGny3rciXhXxUTN7mmoufyz/&#10;r0JOf5s6Nhi4HxhgZh/mM74kKp9T4qt0XyWeM/MUcJL3Xn//aarkb/8D0qxTtWICXAWLgAHAb4Bz&#10;iEeTcmg+JB45AmwlvkQkafDeNwdeIL6fuyB1eGU1lj+WlMpy6r0fAgwHepqZvhyl6QD/TzukXjsW&#10;eMrMbsxXfEl0gJy+Rpp1qjYW81HAr7z31wE7ie9HyKEZBvzWe18CfJZ6Lum5hXjm6jjv/XggIr4H&#10;ea+WP662ijktAE4BNgOzvfcR8IqZTchjjElT2f/T/ma2L79hJVplOR0K/DqdOqXlXEVERBKuNt4z&#10;FxERqVFUzEVERBJOxVxERCThVMxFREQSTsVcREQk4VTMRUREEq42/s5cJK+89wHwQ+Ay4t8+1wXm&#10;AuPN7LNqtPcI8KaZVWnlLe99H+AXxL9n/UoqhndSL/+MeLGKKreXZqw9gPvMrEOa54XAUWa2o8Lx&#10;HwPtzew7GQxTJHFUzEVy70HiddZ7m9kn3vsvAU8S70Q3NNudm9lLQEcA7/1tQFMzu6Hsde/9gCyH&#10;UJ3FLb7oHC2WIbWeirlIDnnvjyMekbcws90AZrbXe38N0DVV2N8FupjZxtQ584n34H459W834h3A&#10;5pjZ2Artn0S8zWcT4hH3NDObWY1Qu3nvBwHNgTXAZak4PwWeA04FrgD2EK/N/y/9ee+PAB4hXrc7&#10;BJab2TWptou8908Rb+tYDxhmZn/y3h8J/BI4PXXOPOAWMwtJbeCR2vv5XuId5LYB76M160V0z1wk&#10;x84A1pYV8jJm9r6ZzTGzvcBMUkvieu/bAG2JL8PfDtQzs3bEI+tu3vtzytrw3hcQ77p0k5l1BnoC&#10;o733XaoRZzHQO9X3McAlqeN1gefM7CRgFfESs5X1dzHQwMzOALqk4jsh1UZL4E4z6wjMAH6SOn4v&#10;8b7OHYCvA6cRL79c3gjiLwhfA/oBravx2URqHBVzkdwKOfjf3QPAlaniPAx4yMwioA/xdpOYWYmZ&#10;9UptwlKmLdAGeNh7vxJ4BahP6pJ6muaY2b7UqHgN8da2ZV6rQn+vAad47xcQb994j5ltSp33dzNb&#10;lnr8l3JtnwfcV/b5iG9H9E+9VnYpvQ/wpJntN7M9xBtRiNR6uswukltLiLeJPKL86Nx73xKYDgwy&#10;s79571cDFxFfyv566m2llLs/7L0/hvgyd5kC4H9So+Gy9zSjepehS8o9jvjXfap3Haw/M/vMe/9V&#10;4tF6b+Al7/31xDvsHajtil9yAqCwwrGKsZRW9QOJ1GQamYvkkJltJR5NPuy9LwIod694e7ndp+4H&#10;pgCLzWxb6tgfgaHee+e9r0d8ifuccs2/BXzqvb8i1W4r4lH1QfdCrqYD9ue9vxaYaWYvmtktxFs8&#10;tk+d5yptLbUNZKqtesRblc6vcM484Nve+3re+/rA4Ax/JpFEUjEXyb3vE29p+rr3fgXwBnERLL91&#10;7FygAfEl9zITiEe1q4DlwFwzm1P2YurS9IXA97z3q4gL361m9kaa8VWcHR5V9vgg/T0GBN77dd77&#10;pUAR8US5ytovcwPQ3Hv/ZuozrgcmVThnOvFnXwMsADZVbESkNtIWqCKHIe99V2B6ur/HFpHaSffM&#10;RQ4z3vuZQA/gyjyHIiIJoZG5iIhIwumeuYiISMKpmIuIiCScirmIiEjCqZiLiIgknIq5iIhIwqmY&#10;i4iIJNz/AuSj76YbXbeyAAAAAElFTkSuQmCC&#10;">
+
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAfMAAAGMCAYAAADOe0tfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz&#10;AAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xm8TfX+x/HXd51zzLNIJ1HqnpWcktykKBlzZWhcSTTd&#10;q1xJt8GtpFBSrlQkQ7q3SdIqSeRqMKRyJdJAWRpcDZpuSnRwOOv7+2NtfocM27H32Wd4Px8PD2ev&#10;vfZ3fda3k8/+ftdnfZex1iIiIiLFl5PqAEREROTgKJmLiIgUc0rmIiIixZySuYiISDGnZC4iIlLM&#10;KZmLiIgUc0rmIiIixVx6qgMQKUyu654BLAAmBEHQN9/2y4D7giColYRjtgLmA5WCIMiJY//jgZpB&#10;ECw4iGNWAW4GLgCOAL4DZgHDgyD4rqDtFiCOQ4D2QRA8E3s9H3g3CIK/u65rgMeAC4EfgCHAyCAI&#10;aifguLv0oeu6IdA5CILZB9v2Ho5VEXgQ6AaUAf4NXF+Y/SyikbmUNpcAq4HuruuW3e29ZK6gdCBt&#10;zwCOK+iBYgn0HaAV0BdwgStify91XffogrZdAP8Azs33+lxgaOznU4FLY9taAFM5iPPeze59WAd4&#10;LUFt724C0BT4E3AaUBvwk3QskT3SyFxKDdd1yxCNVP8GTATOB6akNKg9Mwf5+QeBX4BWQRDkxbZ9&#10;5bruQmAO8E/gzIM8Rrx2OZcgCH7J97I6YIMgeDXftq1JOu4PCWp3T3KAa4IgWAbguu6DwHTXdU0Q&#10;BFpiUwqF0XKuUlq4rnse8CxwKPAUUDYIgnax9y4DRgIPADfGPvIkcFMQBKHrumlESfICoCqwDLgh&#10;CIJ3Y58/GriPaDQcAi/E3t8Um2afB1QGagFrgOwgCD7Od+z7giCoFZuGbkU0kn8jCII2ruseCjwE&#10;dAQ2AS8DNwZB8OsezrE60ZT6uXuaUnZdtzmwCGgUBMEnruuuIZraHhd7v37++FzXrR3rk/ax8/4K&#10;uDsIgsdi+88H3gBOBDoA/wOGBEHwL9d1BwODY4e2QRCk7ZhmB1YSTbETO9ehwFryXepwXfcEYBTQ&#10;HFgPjA+C4N7YeycD9wCnEA1KPgD6B0GwZC99uHOa3XXdDGAgcBlwGLA01p9L9nFOQ4Mg+Ofu/bmH&#10;/j0MmET0u9V+f/uLJIqm2aU0uQR4OwiC9UTJ9sxY8trhEKJ/vM+M7dsD+HvsvWuBLkBXounb1cBz&#10;AK7rVgPeIhpVtiCaNm5JNALekz19g96x7Tzga6Jkc15s23QgjyhxdQYaEE1J70lTouT2nz29GQTB&#10;YmAL0XTw3uSP7ymifmkNNCSavh7vum7+2oK/A7OJ+mU6MC72/n1E080ziaa585sK9Iodq05s353H&#10;dl23JjCXqC/+CFwF3OK67uWu61aKHe894HiiftlENNsCe+7D/MYCVwJ/JUrYK4HXYl+a9nZOD+92&#10;zr/juu5Y4JtYPNfta1+RRFMyl1LBdd2qQCdgWmzTi0Qj6Mvz7bYd6BEEwYogCF4BhhFdcwY4kigJ&#10;fhUEwX+BG4DLYkVcPYn+X7o0CIJPgiB4M9buhXu5Pr3XafQgCH4mStwbgyD4xXXd1kA20CvW9ntE&#10;SbCj67oN99DEIbG/N+7tGESj3EP28X7++GYCVwdBsDIIgi+A4URFXln59pkfBMEjsX4ZFHu/cRAE&#10;vwGbga1BEPy423luJboUQBAEP+6hMLA7kAv0DiKvECXfTUAFYARwSxAE/w2C4ENgPFE//a4P8zca&#10;+z24EvhbEASvBEEQxNr9Cui3v3PaR58BjAFOJhrVz419IREpFErmUlpcRPQP8nSAIAh+IvpH97J8&#10;+3wTBMG3+V4vAw6PVYaPByoRXXt+E7ga+Dh2TbQh8H4QBLn5PvsuUTJqdJBxHwdUBH52XXej67ob&#10;gYDoi8ixe9j/p9jfdffRZlViiTQO44HmruuOcV13DvAx0eg5Ld8+n+74IQiCHV8iMuJsf28aAh8G&#10;QbA9X9vPBEHwfOz696PANa7rPhqrBXiC+P49y4rttzhfu5bYpYd8+x3wOQVBsDp23bwn0ezIRXHE&#10;I5IQKoCT0uKS2N9rXNfdsc0AxnXdtrHXebt9Zkdy2BYEQeC67lHAWURVy/2Bfq7rnkI0Yt8Tw65J&#10;D/Y8xb6v/w/Tgf8C7fj9iP77Pey/lGiGoVnsc7twXbcp0ZeDd/cST3q+fQ3wCpBJNC0+j2hKOtjt&#10;M7n83sEW8eXurY3YdeklwCqi28CmEtUiTI6j3S17addh1/9WcZ2T67rliGZ8Xg2CYBNAEARbXNf9&#10;gn3PfogklEbmUuK5rluP6Br2YKKp0h1/mhJN214Z27Vu7Pr3DqcBa4Mg2Oy6bk/goiAIZgVBcA3R&#10;bV61Y+1+Apy4261uzYgS4ye7hbMjSVTOt233qfj8CfYTomS6KQiCL2JT3XlExXi/ux87NsXsA4Nj&#10;hV64rtvCdd0PXdftDNwFLItN1++IZ/dYdhy/CdAG+FMQBHcGQfAiUQU6xJ+sC1phuxrIjhUeEjuP&#10;O1zXfRa4mOgLVvsgCO4PguB1onvp4znuZ8A2fl8zcCrRrENBTCGqp9gRZxWiGYAVBWxP5IBpZC6l&#10;QU+ia7djdq8Ad133CeAvRCPVdOAZ13VvJkpqtxItvAJQBbjTdd2fiP7R70yU0N4D1gF3AE+6rnsn&#10;UBMYB7wWBMGqWGHVjuT3PdH12Rtd172F6EvF5bvFuwloGCu4ei12vGdd172JaHp9LNGU/3/3cr5/&#10;I7qEMN913aHA58DbwEtESS5/InsXuDQ2hV6OKNnvSITfEasjcF33aaIvMKNj7+9+j/7ebAIaua5b&#10;PwiCtXF+BuBpokVkxrmuOwo4JnZe1xF9ATnUdd2ziRJma+A2iG4/jF3u2NmH+a/Xx76YPQTc77ru&#10;b0SV+9cB9Ymq0A9IbBQ+CbjXdd1viS5z3Btr98UDbU+koDQyl9KgBzB1T7dyESXGMkSV6B8TJbeF&#10;RNeK7wuCYBJA7NatsbHtq4iqqy8IguDzIAg2E1XBVyWa/n2OaJW58/Mdx8basUTJuyHRlPV1RF8a&#10;8htN9AVkTmz/rkRJYl7szzqg097uYY7VA5wai2EsUcLrTHSr3QvA1NgoHaIk+A1R9fvjRLMXYayd&#10;dbHz7E00Q/Ag8DDwIdGsxt7kj+txotu/VsZuc4tL7Dr1n4jqAt6PHXdoEARPEc08TCK6te2DWHx/&#10;iR13R1w7+3APMd1KdIviY0R1EQ2BM2OzHrvvu6dz2t2NRFP9k4muvW8Gzg6CIIzzdEUOWtLvM/c8&#10;7xTgXt/3W3uedxLRP4ZbgPd939ftGyKFzHXdDkTT1PNTHYuIJEZSR+ae5w0gtoBCbNNEoL/v+62A&#10;DZ7n9Ujm8UXk94IgeFWJXKRkSfY0+2fsui5zXd/334n9vIioeEhEREQOQlKTue/704kKaHb43PO8&#10;02M/dyG6RUZEREQOQmFXs18JjPY8Lx14k73fn5ufFo8XEZHSKO71Ggo7mZ8N9PB9/2fP88YQrX28&#10;X+vWrUtoEJmZmQlvs7RTnyae+jTx1KeJpz5NvMzMzAP+TGHfmvYpMM/zvLeADb7vz9nfB0RERGTf&#10;kj4y931/LbFFKnzfnwXMSvYxRUREShMtGiMiIlLMKZmLiIgUc0rmIiIixZySuYiISDGnZC4iIlLM&#10;6RGoIiJSLLz//vvceeedHHnkkQD89ttvZGZmMmjQINLS0nbuZ61l/PjxrFmzhtzcXMqXL891113H&#10;YYcdtt9j5Obmcvfdd/PLL79QoUIFbrnlFqpWrbrLPs888wzz5s2jYsWKXHTRRZx66qk73/vyyy/p&#10;27cv06dPJyMjg3fffZdJkyZRvnx5Tj75ZHr27JmYztiNRuYiIlJsNGnShPvvv5/777+fiRMnkpaW&#10;xttvv73LPkuWLOGnn35i5MiRjB49mi5dujBu3Li42p8xYwYNGjRg9OjRtG/fnqeeemqX99esWcO8&#10;efMYP348//jHP3jsscfIzc0FICcnh/Hjx1OmTBkg+lIxatQo7rzzTkaPHs2XX37JihUrEtALv6dk&#10;LiIixdK2bdtYv349lStX3mV7tWrVWL16NfPnz2fDhg20aNGCIUOGAPDGG2/Qu3dvBgwYwJAhQ3jl&#10;lVd2+exHH31Es2bNADjllFNYtmzZLu+vXbuWE088kfT0dMqUKUPdunX5/PPPARg1ahS9e/emXLly&#10;AGzYsIHKlStTp04dALKzs/noo48S3g+gaXYRESmA8LnHsMveZl1aGnl5eQlp0zRtgXPhFfvcZ/ny&#10;5dxwww2sX78ex3Ho0qULTZo02WUf13W58cYbmTlzJg899BC1a9emb9++NGrUiPHjx/Poo49SsWJF&#10;brnllt+1n5OTQ8WK0TPAKlSoQE5Ozi7vN2jQgClTprB582Zyc3NZuXIlXbp04YknnqB58+Y0aNAA&#10;a6NHilSrVo2tW7fy1VdfkZmZyTvvvMMxxxxzMF20V0rmIiJSbDRp0oTbb7+dX3/9lQEDBuwc9eb3&#10;xRdfcMQRR3D77bcDsHTpUoYMGcI///lPqlSpQqVKlQBo3Ljx7z5boUIFNm/eDESJfce+O9SrV49z&#10;zjmHm2++mdq1a9OwYUOqVq3Ka6+9Ru3atZk9ezbr169nwIABPPjgg9xyyy088MADlClThiOPPPJ3&#10;198TRclcREQOmHPhFXDhFSl70EqVKlUYOHAg119/PY8++ig1atTY+d6yZctYu3YtN954I8YY6tev&#10;T/ny5alevTpbtmzhl19+oVq1agRBwGmnnbZLu9nZ2SxevBjXdXnnnXc4/vjjd3l/w4YN5OTkMGbM&#10;GH777Tf+/ve/c9RRRzF58uSd+1x88cXcd999ALz77ruMHDmStLQ07rjjDv70pz8lpT+UzEVEpFiq&#10;X78+559/Pg899BCDBw/euf28885jwoQJ/OUvf6FSpUoYY7jtttsAuP766xk4cCAVK1Zk69atv2uz&#10;W7du3HPPPfTv35+MjAwGDRoEwHPPPUfdunU59dRT+fLLL/nrX/9KRkYGffr0wZhdn1RqjNk51X7I&#10;IYfQp08fypYtS7t27ahfv35S+sLsOGARZvUI1KJPfZp46tPEU58mXnHu00mTJlGvXj3OOuusVIey&#10;i3yPQI37eeaqZhcRESnmNM0uIiKlUu/evVMdQsJoZC4iIlLMKZmLiIgUc0rmIiIixZySuYiIJIW1&#10;kJOTx/btRf6uqWJPyVxERBIqL8+ycuWv3H33B3Tt+io9esznlVfW8b//5Sb8WNOnTz/oNq655hq+&#10;//77A/7cl19+yfXXX3/Qx08EVbOLiEhCLVz4A5ddNo+8vP8fkb/99ne0b1+Xf/zjFGrXLpuwY02e&#10;PJlzzz03Ye0dqN0XjEkVJXMREUmYr7/eTJ8+C3dJ5Du89trXLFp0FOecc0QB2/6aESNGkJ6eThiG&#10;nHTSSWzcuJHRo0fTu3dvRo4cyW+//cZPP/1Et27d6Nq1K9dffz3HHHMMa9asIScnhyFDhlC7dm0e&#10;ffRRli5dSq1atfj1118B+PHHH3nwwQfJzc1l/fr1XHnllbRo0YIrr7ySunXrkpGRwTXXXMOwYcMA&#10;qF69+s7YHn30Ud5//33CMOSMM86ge/fuBTrHglIyFxGRhFm9egObNm3b6/sPPfQR7dplUqlS2gG3&#10;vXTpUho2bMjVV1/NRx99RNWqVZk5cybXXXcdn376KW3btqVly5b89NNPXH/99XTt2hWAhg0bcs01&#10;1/DPf/6TuXPnctJJJ/HRRx8xYcIEcnJy6NWrFxBNm3ueR+PGjVm5ciWPP/44LVq0YPPmzVx22WUc&#10;ffTRjBkzhrZt23L22Wczf/58Zs6cCcC8efN44IEHqFGjxu8eq1oYlMxFRCRhNm7ceyIH+P77zWzZ&#10;klegZN6pUyeeeeYZ/v73v1OpUiX+/Oc/73yvevXqPP/88yxcuJAKFSqwffv2ne/teOxorVq1+Pnn&#10;n/n6669xXReInpJ21FFHAVCzZk2eeuopZs+eDbDLo12POCKaTfjqq6/o3LkzED2UZUcyHzhwII88&#10;8gg///zzzuehFyYVwImISMLUrl1+n++fcEJNKlUq2Djy7bff5oQTTmDUqFG0atWKZ555ZucDTXzf&#10;p1GjRgwcOJAzzzyT/M8d2f26dv369Vm1ahUAmzdvZu3atQD861//4qyzzuLWW2+lSZMme2zjyCOP&#10;ZMWKFQA729i+fTtvvPEGt99+O/fffz9z5szhhx9+KNA5FpRG5iIikjBZWVWoX78Sa9du2uP7ffs2&#10;oly5go0jXdfl3nvv5amnnsJau7MKffjw4XTq1IkxY8Ywf/58KlasSHp6Otu2bdtjgdoxxxxDs2bN&#10;6NOnDzVr1tx57fvMM89k/PjxTJkyhUMOOWTntfT8bfTs2ZO7776bBQsW7HyWenp6OpUrV6Zv376U&#10;K1eOk08+mdq1axfoHAtKT02ThFCfJp76NPHUp4m3pz4Ngo1ccslcvv02Z+c2Y2Dw4D9yySVHU6HC&#10;gU+xlyYFeWqaRuYiIpJQrluZWbP+xCef/MKqVT9TvXo5TjyxJg0aVKRMGV3dTQYlcxERSbg6dcpS&#10;p86htG59aKpDKRWSnsw9zzsFuNf3/dae550IjAe2Aat93/9Lso8vIiJS0iV1vsPzvAHAJGDHcj93&#10;AEN83z8DKOd53tnJPL6IiEhpkOyLF58B+dfZWw4c4nmeASoTjdBFRETkICQ1mfu+Px3Ynm/Tp8AY&#10;YCVQG1iQzOOLiEjqGGtJz8nB2b59/zvLQSnsArjRQAvf91d5ntcXuB/ot78P5SvTT5hktFnaqU8T&#10;T32aeOrTxNu9T/Nyc9n6n/+Q9txzpM+bR1ijBtuvvhqnZUvKHHlkgR9Okpuby4wZM7jwwgvj/szS&#10;pUupUqUKWVlZBTpmcVHYyfwnYGPs53XAafF8SPeZF33q08RTnyae+jTx9tSnlebPp/Jll2Fiy6Gm&#10;ARlvv01u+/b89I9/kFvABVW+++47pkyZQosWLeL+zFNPPUXr1q2pVKlSgY6ZCgX5wlnYybw38Kzn&#10;eduA3NhrEREpIcp+/TWV+/TZmcjzK/Paa5RdtIjcc84pUNuTJ09m7dq1PPHEE6xZs2bnCm3XXnst&#10;Rx11FCNGjGDdunXk5uZy3nnnUb9+fZYsWcKnn37KUUcdRa1atQ7q3IqypCdz3/fXEhuB+77/NtAy&#10;2ccUEZHUyFi9GrNpz0u5ApR/6CE2t2vH9gKMlHv27MmaNWvIzc3lpJNOomvXrnzzzTeMGDGCESNG&#10;8NFHH/Hwww8DsGzZMrKysmjWrBlt2rQp0YkctGiMiIgkkNm4cZ/vO99/j7NlCxzEtPcXX3zBe++9&#10;x4IFC7DWsnHjRsqXL88111zDqFGjyMnJoV27dgVuvzhSMhcRkYQJ93M9fPsJJ5BXwETuOA5hGFKv&#10;Xj3at29PmzZt+OWXX5g9ezbr169n9erV3HnnneTm5tK9e3c6dOiAMYYwDAt0vOJEyVxERBJmW1YW&#10;2+vXJz32WNHdbenbl7xy5QrUdrVq1cjLyyMnJ4cFCxYwc+ZMcnJyuPzyy6lRowbr16+nX79+pKWl&#10;cdFFF+E4Dg0bNmTSpEkcdthh1KtX72BOrUjTU9MkIdSniac+TTz1aeLtqU/LBwFVL7kE59tvd26z&#10;xpAzeDCbLrmEvAoVCjvMYkVPTRMRkZTb7LrkzZpFmU8+IW3VKmz16mw78US2NmhAWKZMqsMrkZTM&#10;RUQk4XLr1CG3Th1o3TrVoZQKerCsiIhIMadkLiIiUswpmYuIiBRzSuYiIiLFnJK5iIhIMadkLiIi&#10;UswpmYuIiBRzSuYiIiLFnJK5iIhIMadkLiIiUswpmYuIiBRzxSKZ5z08HPvt16kOQ0REpEgqHg9a&#10;eX8x4YdLMC07YLpejKlaPdURiYiIFBnFYmTu9B0ItQ/DLpxDeNvVhDOmYLfkpDosERGRIqFYJHPT&#10;pDnOkLGYXn2hXHnsrKmEA68mnD8bu317qsMTERFJqWKRzAFMWhrOGR1x7p6I6dYDcnOxUyYQDu6H&#10;XfY21tpUhygiIpISxSaZ72DKlsPp3B1n+ERM67Php+8JJ4wgvGcAdvWKVIcnIiJS6IpdMt/BVKmG&#10;0+NqnKEPY5q2gDWrCUcOJG/sMOy6L1MdnoiISKEpHtXs+2AOzcT0uRn7RUA47XH4YAnhh0sxLdtF&#10;le/VaqY6RBERkaQqtiPz3ZkGLs5Nw3H63Q6H1cW++WpU+T79KWzOb6kOT0REJGmK/cg8P2MMND4Z&#10;5/iTsIvmYWc8jZ39HHbhHEzn7phWHTHpGakOU0REJKFKzMg8P+Ok4bRsjzNsIubcXpCXh506ifCO&#10;awiXLMSGYapDFBERSZgSmcx3MGXL4nS6EOfuRzBtu8D6/2En3cf3N1yOXfXhnj9jTCFHKSIicnCS&#10;Ps3ued4pwL2+77f2PO8Z4FDAAEcC//F9v0eyYzCVq2C698a27YJ9cTLbliyEUYMguynO+ZfhHHo4&#10;5Vavpsy8eaSvWMH27Gxy27RhS1YWNkPT8iIiUrQlNZl7njcA6AVsAvB9/+LY9mrAPOBvyTz+7kyt&#10;OpjeN3FIj958P2EkrFhGuPI90jOPptLk6WRszgWg7KxZVBgxgk1jxrCpSxcldBERKdKSPc3+GXDu&#10;HrYPBR7yff+HJB9/j8r8oSHODXfhXDcYp+ah5H7zGd+f0Yhf3MMJ09MAMNZSqX9/yq1enYoQRURE&#10;4pbUZO77/nRgl8XTPc+rBbQBHk/msffHGIPJbkrVw7Kp8cEanNztbDy6Dt+emc3Go2pjHYOxljLz&#10;56cyTBERkf1Kxa1pFwBTfN+PezH1zMzMhAeRmZnJ9u3bsStXkvHNesp/+zOb6tfm12Pq8EvDI9hY&#10;vzZVV68jfcUKateuTXp6ibqLLymS8d+ptFOfJp76NPHUp6lXWBkqf4l4O+CuA/nwunXrEhpMZmbm&#10;zjarZmeTMWsWTmipsuZ7Kn79PzYeXYeN9Wuz/sSjSCuzEbvgFcxxTX7XjjFGD3iJyd+nkhjq08RT&#10;nyae+jTxCvLlqLCSef6MlwV8UUjH3a/cNm2oMGIEJpaU07blUW3VN1Ra+yMbsjLJOdzAA4PhuBOj&#10;yvfD6qnyXUREihRTDEaWNpkjc7NtG5VmzqRS//47EzqANYZNDz3ExsaNyJvxNHy8HICMzAbUfPol&#10;MjZv3XXfUl75rm/niac+TTz1aeKpTxMv38g87oVPSv2FYJuRwaYuXdjuupSZP///R9utW7MlKwsy&#10;Mki7fij24+UweQLb1n3Bd2ccR6W1P1Ll829J25a3s/J9u+uyuVGjVJ+SiIiUMqU+mUOU0Dc3asTm&#10;Ro32eh3cHNeEKnUaYV5bxIasTDY1OJTfjqhJlc+/o9J/f8AJo8p3JXMRESlsSua72dtlB2MMGStX&#10;Unbdeip89zOb6tfi16MPY8OxddkUq3xP++gjFcWJiEihK9FrsyeStZbt2dkAmNBSec0PHLZgBZU/&#10;/46wTDrrGx/J+jIbCT9cqmQuIiKFSsn8AOS2aYPN9yAWZ3se1YJvqPPGCip8/RN5W34jHDOUcNQg&#10;7H8/TWGkIiJSmiiZH4AtWVlsGjNml4QOkLZ1O2Wuuom020bB8X+E4CPCu28kfGQk9sfvUhStiIiU&#10;FrpmfgDiqnzvfwd21YeEzz+OffdN7Hv/wZz5J8zZF2EqV0n1KYiISAmkZH6A4qp8P/YEnIH3YZe9&#10;jZ3+FHbuTOyiuZizzsO064YpWzYFkYuISEmlafaDsK9CN+M4OCefjnPnw5juvSEtHfviZMJBVxO+&#10;+So2L68QIxURkZJMyTzJTHoGTtsuOHdPxHS6EHI2YZ8cSzi0P/aDd1X5LiIiB03JvJCYChVxzu2F&#10;M2wi5vQO8N03hGPvIrxvIPaLINXhiYhIMaZkXshM9Zo4l/bDGTIGGjeD1SsJ7xlA3oR7sd9rfWMR&#10;ETlwKoBLEZNZj7R+g7CrVxI+/xgsW0T4/juYM87CdO6OqVIt1SGKiEgxoZF5ipmsRji3jsTpczPU&#10;PBQ7fzbhwKsJZ07Fbtmc6vBERKQYUDIvAowxmKYtcIaOxfToA2XKYF+aQjioD+Ebc1T5LiIi+6Rk&#10;XoSY9HSc1p1whk/EdO4OWzZjJ48jHHItdvliVb6LiMgeKZkXQaZcBZxuPaLb2Vp1hB/WEY4bTjji&#10;Zuxnn6Q6PBERKWKUzIswU7U6Ts++OEPHQpPm8PkqwhE3kzduOPa7r1MdnoiIFBGqZi8GTJ26pPUd&#10;iP3sE8Jpj8PyxYQfLMG07IDpejGmavVUhygiIimkkXkxYo5piPP3e3H6DoTah2EXziG87WrCGVOw&#10;W3JSHZ6IiKSIknkxY4zBNGmOM2QspmdfKFceO2tqdDvb/NnY7dtTHaKIiBQyJfNiyqSl4bTqGBXJ&#10;desBubnYKRMIB/eLntamyncRkVJDybyYM2XL4XTuHt3O1roT/PQ94YQRhPcMwK5ekerwRESkECiZ&#10;lxCmSjWcHn1whj6MadoC1qwmHDmQvLHDsOu+THV4IiKSRKpmTyBjTMqnt82hmZg+N2O/CKLK9w+W&#10;EH64FNOyXVT5Xq1mSuPbl4L2X1HodxGRVFIyP0jbtllWr97IvHnfsGLFerKza9CmzeFkZVUmI8Ok&#10;LC7TwMW5aTh8uJRw2uPYN1/FvrMA064b5qzzMBUqpiy2/Araf0W130VEUsEUgxGNXbcusY8GzczM&#10;JBFtbttmmTnzK/r3f4v83WgMjBnTki5djigSicXm5WEXzcW+NAV+WQ+VKkdPZmvVEZOekZBjFKRP&#10;C9p/xaXfD1aifk/l/6lPE099mniZmZk7foz7HzJdMz8Iq1dv/F1CAbAW+vd/i9WrN6YmsN2YtDSc&#10;0zvgDJuIObcX5OVhp04ivOMawiULsWGYkrgK2n/Fpd9FRAqLkvlBmDfvm98llB2shfnzvyncgPbD&#10;lC2L0+lCnLsfwbTtAuv/h510H+Hwm7CrPiz0eAraf8Wt30VEki3p18w9zzsFuNf3/dae59UCJgHV&#10;gDTgUt/31yQ7hmQwxrBixfp97rNixc9FsjjLVK6C6d4b27YL9sXJ2CULCUcNguymOOdfhql7ZPJj&#10;KGD/FedSAcQ6AAAgAElEQVR+FxFJlqSOzD3PG0CUvMvGNv0DmOz7/pnA7cCxyTx+Mllryc6usc99&#10;srOrF+mEYmrVwel9E85to+DYE2DFMsI7ryN8bDR2/Y9JPXZB+68k9LuISKIle5r9M+DcfK9bAHU9&#10;z3sN6AEsSPLxk6pNm8MxeylPMAZatz68cAMqIHPkH3BuuAvnusGQWQ+7aC7hoL8SPv84NmdT0o5b&#10;0P4rKf0uIpIoSU3mvu9PB/IvFn4ksN73/fbAV8AtyTx+smVlVWbMmJa/SyzGwEMPnU5WVuXUBFYA&#10;xhhMdlOcOx7EXHEdVK6CfeUFwluvInz1Rey2bQk/ZkH7ryT1u4hIIhT2feY/ATNjP88EhhXy8RMq&#10;I8PQpcsRuG5n5s//hhUrfiY7uzqtWxff+52Nk4Y5rS32jy2x81/Gvvwc9rl/YefNwpxzCaZZK4yT&#10;mO+ABe2/ktjvIiIHo7CT+ZtAJ+Bp4AxgZTwfynfPXcIkss369aFt2yzCMMRxHJwEJbuUu6IfeRf0&#10;YuOzj7Fx5rPYfz5A+oLZVLviWso1af673QvapwXtvxLb7/kk43e/tFOfJp76NPUKO5nfBDzqed5f&#10;gQ1E1833q6guGlNqdPJwmrXCzniabe+8wY+D+sFxJ0aV7/WOBtSnyaA+TTz1aeKpTxOvIF+OtAKc&#10;HBD75ReE056Aj5cDYJqfiTmnJ4cff6L6NMH0e5p46tPEU58mXkFWgNPa7HJATL0GpF0/FPvx8qja&#10;ffEC7NK3+LnLRdhWnTAVVXwmIlLYSt5FRikU5rgmOIMewPz5Bqhag03TnyYceBXhnGnY3K2pDk9E&#10;pFRRMpcCM46D0/xMnLvGU+0vfwMMdtoThLf/lfDtudgwL9UhioiUCkrmctBMRgaVz+2Jc88jmI7n&#10;w8ZfsY+PJrzzb9iPlmk1NhGRJNtvMvc876TCCESKP1OhEs75l+EMG485rS2s+5JwzFDCUYOw//00&#10;1eGJiJRY8YzMn056FFKimBq1cK64DueO0XD8HyH4iPDuGwkfGYn98btUhyciUuLEU83+oed5PYC3&#10;gJ0Ldfu+v+9HV0mpZ+oeSVr/O7CrPowq3999E/vefzBn/glz9kWYylVSHaKISIkQTzLvBly42zZL&#10;9AhTkf0yx56AM/A+7LK3sdOfws6diV00F3PWeZh23TBly+6/ERER2av9JnPf98sVRiBSshnHwZx8&#10;OrZJc+wbc7Czno2epb5gNqZrD0yLthhH3w9FRApiv8nc8zwHuAHIBq4F+gH/8H1f9x3JATPpGZi2&#10;XbCntsG+8gL29RnYJ8diX5uBc/7lcMIfMXt7vqmIiOxRPAVwI4ETgFNi+3cEHkhmUFLymQoVcc7t&#10;hTNsIub0DvDdN4Rj7yK8byD2iyDV4YmIFCvxJPO2wOXAFt/3NwAdgPbJDEpKD1O9Js6l/XCGjIHG&#10;zWD1SsJ7BpA34V7s91rvWUQkHvEk822+74c7Xvi+vxXYnryQpDQymfVI6zcIZ8BwOCoLli0iHHwN&#10;4ZQJ2F9/SXV4IiJFWjzV7Cs8z7sGSPM8zyW6fv5+csOS0spkZePcOhLeW0T4wpPY+bOxi+ZjOp6L&#10;aX8OpqzqMUVEdhfPyPw64CTgUOBtoBLwt2QGJaWbMQbTtAXO0IcxPfpAmTLYGVMIb7ua8I052DzV&#10;XoqI5BfPrWm/An8uhFhEdmHS0zGtO2FPPRP7yovYV6djJ4/Dvv4SznmXwomnqPJdRIT4bk2rDYwm&#10;KnrbBswGbvR9XxcypVCYchUw3XpgW3XEzpyKfetVwnHD4ehjcS64AnNMw1SHKCKSUvFMs08CvgCa&#10;AacDPwMTkxmUyJ6YajVwevXFGToWmjSHz1cRjriZvHHDsd99nerwRERSJp4CuCN93++W7/VNnud9&#10;lKyARPbH1KlLWt+B2M8+Jnz+cVi+mPCDJZiWHTBdL8ZUrZ7qEEVEClU8I/N1nucdteOF53l1gW+T&#10;F5JIfMwxx+HcPAKn70CofRh24ZyoSG7GFOyWnFSHJyJSaPY6Mvc8bybRA1VqAe97nvc6kAe0Bj4s&#10;nPBE9s0YA02a45xwMvat17Azn8HOmop949+YLhdjTu+ASY9nAkpEpPja179yz+9l+8vJCETkYJi0&#10;NEyrjtjmZ2JfexE7Zzp2yoRY5XsvOOk0Vb6LSIm112Tu+/4T+V97nlch+eGIHBxTthymc3fsGR2j&#10;EfrCVwgnjICjsnAuuByTlZ3qEEVEEi6eW9OuB+4Gdjx02qDnmUsRZ6pUw/Tog23bNXqG+rK3CUcO&#10;hMbNcM67FJNZL9UhiogkTDwXE28AmgOfJzkWkYQzh2Zi+tyM/SIgnPY4fLCE8MOlmJbtosr3ajVT&#10;HaKIyEGLJ5l/6vu+Ct6kWDMNXJybhsOHSwmnPY5981XsOwsw7bphzjoPU6FiqkMUESmweJL5WM/z&#10;ngVeJVoBDgDf959MWlQiSWCMgcYn42SfhF00F/vSFOzs57AL52A6d8e06ohJz0h1mCIiByyeZH4N&#10;0UNW8hfAWUDJXIolk5aGOb0Dtlkr7NyXsHOmYadOws6diTmnJ+aPLTFOPEswiIgUDfEk83q+7/8h&#10;6ZGIFDJTtiym04XY08/CvvwsdsG/sZPuw776YlT5fuwJqQ5RRCQu8Qw//ut5XmbSIxFJEVO5Ck73&#10;3jh3jcM0OwPWfkY4ahB5o4div/5vqsMTEdmveEbmm4EVnue9C2zdsdH3/a7xHMDzvFOAe33fb+15&#10;3onALGB17O3xvu8/d4AxiySFqVUH0/smbPtuhNOegBXLCFe+hzm1DaZbD0yNWqkOUURkj+JJ5tNi&#10;fw6Y53kDgF7AptimpsAo3/cfKEh7IoXBHPkHnBvugpXvET7/eFQs9+6bmDadMZ0uwFSolOoQRUR2&#10;sd9kvvtKcAfoM+Bc4KnY66ZAlud55wCfAtf5vv/bQbQvkhTGGMhuinPcidjFC7Aznsa+8gL2zVcx&#10;Z3uY1mdjMlT5LiJFQzwrwG0kql7fhe/7Vfb3Wd/3p3ueVz/fpneASb7vL/c8byAwBBgQf7gihcs4&#10;aZjT2mL/2BI7/2Xsy89hn/sXdt4szDmXYJq1UuW7iKRcPNPs+RezLgOcR/T0tIJ40ff9DbGfpwNj&#10;4vlQZmbi6++S0WZpV+L79Ip+5F3Qi43PPsbGmc9i//kA6QtmU+2KaynXpHlSDlni+zQF1KeJpz5N&#10;vXim2dfutmmE53nvAPcV4HiveJ7Xz/f9pUBbYFk8H1q3bl0BDrV3mZmZCW+ztCtVfdrJw2nWCjvj&#10;aba98wY/DuoHx52Ic/5lmHpHJ+wwpapPC4n6NPHUp4lXkC9HB/ygZ8/zjiVaRKYg/go85HleLvAd&#10;cFUB2xFJKXPIoZg/3/D/le8fv0/48fuY5mdGC8/UrJ3qEEWkFDnQa+aGaKr97/EeIDayPy3283Kg&#10;5YGHKVI0mXpHk3b9ndiPl0eV74sXYJe+FRXIne1hKlZOdYgiUgoc6DVzC/zi+/6vSYpHpFgyxzXB&#10;GdQYu2Qh9sXJ2NdmYN9+HfOnC6Jb2sqU3X8jIiIFtNcyXM/z6nmeV48oge/4A1Attl1E8jGOg9P8&#10;zGgluQuvBAx22hOEt/+VcNFcbFjQulERkX3b18h8JVECN/m2WaA80ZeAtCTGJVJsmYwymA7nYFu2&#10;w/57Gvb1l7CPjY7WfD//csg+KbqPXUQkQfaazH3f3+Vin+d5BhgI3BT7IyL7YCpUwpx/GbZ1J+yM&#10;Kdj/zCMcMxSOPSF6kEv9Y1IdooiUEHFVs3uedzgwGagMnOL7/ur9fEREYkyNWpgrrsO270o47clo&#10;zfdhN2BOPh1zbi9MrTqpDlFEirn9Ll3led55wAdE94SfqkQuUjCm7lGkXTcY58ZhUP8Y7LtvEt7e&#10;l3DqJOxG1ZSKSMHtdWTueV55YDRwNtDd9/3XCy0qkRLMHHsCzsD7sMvexr7wJHbuTOyiuZizzsO0&#10;64Ypq8p3ETkw+5pmfw+oT5TQT/A874T8b/q+f38yAxMpyYzjYE4+HdukOfaNOdhZz0a3tC2Yjena&#10;A9OibapDFJFiZF/J/B1gMVAn9ie/3z14RUQOnEnPwLTtgj21TfRUttdnYJ8ci31tBpuvugF7eANV&#10;vovIfhlri3xetlqbvehTnyaG/fkn7MxnsG+9DjaErEY451+OaeCmOrQSQb+niac+Tbx8a7PH/U1e&#10;z24UKUJM9Zo4l/bDGTKGcs1Oh9UrCe8ZQN6Ee7Hf6x9MEdkzJXORIshk1qPW4AdwBgyHo7Jg2SLC&#10;wdcQTpmA/fWXVIcnIkWMkrlIEWaysnFuHYnT52aoWRs7fzbhwKsJZ03Fbt2S6vBEpIiI56lp7wHj&#10;gCm+7+ckPyQRyc8YA01b4DQ+Bfvmq9E19RlTsAv+jelyMaZle0yaVlcWKc3iGZn3A04HPvc8b6zn&#10;eY2SHJOI7IFJT8dp3Qln+ERM5+6wOQc7eRzhkGuxyxdTDIpZRSRJ4q5m9zyvGtADuBFYB4zxff+5&#10;JMa2g6rZiwH1aeLtr0/tL+uxM6di33oVwhCOPhbngiswxzQsxCiLF/2eJp76NPGSVs0eS+S9gKuA&#10;DYAPXOp53pMHGKOIJIipVgOnV1+coWOhSXP4fBXhiJvJGzcc+93XqQ5PRApRPNfMnwY6AbOAv/q+&#10;/5/Y9vHAD8kNT0T2x9SpS1rfgdjPPiZ8/nFYvpjwgyWYlh0wXS/GVK2e6hBFJMnieWraSuBvvu//&#10;mH+j7/vbPc9rkZywRORAmWOOw7l5BLz/DuELT2AXzsG+swDT/hzMWedgylVIdYgikiRxXTP3PK8T&#10;cBaQB8z0fX9+sgPLR9fMiwH1aeIdTJ/avDzsW69hZz4DG36GylWjyvfTO2DS43rycYmk39PEU58m&#10;XlKumXueNxgYRXStPAeY6Hle/4IEKCKFw6Sl4bTqiHP3REy3HpCbi50ygXBwv+hpbap8FylR4vmK&#10;3gto6vv+BgDP80YBi4AxyQxMRA6eKVsO07k79oyO2FlTsQtfIZwwAo7KwrngckxWdqpDFJEEiKea&#10;/SdgY77XvwCbkhOOiCSDqVINp0cfnKEPQ9PTYM1qwpEDyRs7DLvuy1SHJyIHKZ6R+VJghud5E4Ht&#10;QE/gS8/zzgPwff+FJMYnIglkDs0krc8t2C8CwmmPwwdLCD9cimnZLqp8r1Yz1SGKSAHEk8yPi/19&#10;427bryV6rrmSuUgxYxq4ODcNhw/fJZz2RLRM7DsLMO26Yc46D1OhYqpDFJEDsN9k7vt+awDP89IB&#10;4/v+tqRHJSJJZ4yBxs1wsptiF83FvjQFO/s57MI5mM7dMa06YtIzUh2miMQhnkVjagNPAG2AdM/z&#10;3gB6+r6vexFESgCTloY5vQO2WSvs6zOwr7yAnToJO3cm5pyemD+2xDh6wKJIURbP/6FjgcXAoUBt&#10;4E1gfDKDEpHCZ8qWxTnbw7n7EUzbLrD+f9hJ9xEOvwm76sNUhyci+xDPNfMs3/e9fK8He563MlkB&#10;iUhqmcpVMN17Y9t2wU5/Cvvum4SjBkF2U5zzL8PUPTLVIYrIbuIZmWd4nlduxwvP8yoQFb7FxfO8&#10;UzzPm7/bth6e5y2KP0wRKWymVh2cqwbg3DYK3ONhxTLCO68jfGw0dv2P+29ARApNPCPzqcDrnuc9&#10;Fnt9BfB8PI17njeAaNGZTfm2NQGuPMA4RSRFzJF/wLlxGKx4j3Da41Gx3LtvYtp0xnS6AFOhUqpD&#10;FCn19jsy933/LuCfQAegI/A4MDTO9j8Dzt3xwvO8msAw4LoDDVREUscYgzm+Kc4dD2KuuA4qVcG+&#10;8gLhrVcRvvoidptuchFJpX2OzD3PywDK+r7/GPCY53nHA6t8349rmt33/eme59WPteUAjwI3AFs5&#10;gAXkRaRoME4a5rS22D+2xM6bhZ39PPa5f2HnzYoq35udocp3kRTY61PTPM+rC8wD7vB9f2ps27NA&#10;Y6BNvLemxZL5M0B/4DHgR6A80BD4l+/7N+ynCT0RQqSIytu4gY3PPsbGmc/C9m1kHO1S7YprKdek&#10;eapDEykJ4h707iuZPwN84Pv+vbttHwQc6/t+z3gOEEvmU33fP3W3bc/4vn9aHE3oEajFgPo08YpT&#10;n9r/fY+d8TT2nTfAWjiuSVT5Xq9BqkPbRXHq0+JCfZp4BXkE6r6m2bN93794D9uHAysOIC7Q6Fqk&#10;0BljCu1Rp+aQQzF/vgHbvhvhtCfg4+WEn7yPOaVVNP1es3bS4ivM8xQpqvaVzHP3tNH3/dDzvC3x&#10;HsD3/bXAafvbJiIHb9s2y+rVG5k37xtWrFhPdnYN2rQ5nKysymRkJL9MxdQ7mrTr78R+vJzw+cex&#10;ixdgl74Vq3y/kO1lKiUkvlSfp0hRs69p9vnAlb7vr9lt+9FEU+TNCiE+0DR7saA+TbwD7dNt2ywz&#10;Z35F//5vkf9/a2NgzJiWdOlyRKEmOhuG2CULsS9Ohp9+wJavyMf12nHumAy25P3/OOJA4zuY89Tv&#10;aeKpTxMv0dPso4CZnuf1BxYR3cbWHBhNNNUuIkXI6tUbf5fgILqE3b//W7huZxo1qlJo8RjHwTQ/&#10;E9v0NOz82eS99CyNghnMP6MCo1Yfzwvf1CfEOeD4itp5ihQFe72HxPf9WURJ+1HgN2Aj8DAw3Pf9&#10;ZwonPBGJ17x53/wuwe1gLcyf/03hBhRjMsrgdDiHx44ZwLjPG1KzzBbub/wO/275CmfWWgfYA4qv&#10;qJ6nSCrt8z5z3/enAFM8z6sBhL7v/1I4YYnIgTDGsGLF+n3us2LFzykrFjPG8N4nm5kVNOaJtcdw&#10;Y9YKLjh8DU+evJC3/1eb4atOjCu+on6eIqkS1+oOvu+vVyIXKbqstWRn19jnPtnZ1VOW4PLH9+2W&#10;itz04Sl0fKsj8344jBaH/MDLLV/lb5X/TfjDt3G3szepPE+RVNFSTSIlRJs2h2P2Ui5jDLRufXjh&#10;BrSb3eNbtbEaly9txUWLW/PBLzX4wy8fEN7el3DqJOzGX+NuJ7+icJ4iqaBkLlJCZGVVZsyYlr9L&#10;dMbAQw+dTlZW5dQEFrO3+Bb/fChrLx5KeOVNUL0mdu5MwtuuInzZx27dGnc7ReU8RVJhr7em7eB5&#10;Xr3dNlkgx/f9n5IW1W7H061pRZ/6NPEK0qc77r+eP/8bVqz4mezs6rRuXXTuv95ffHb7Nuwbc7Cz&#10;noVNv0K1GpiuPTAt2mKctLjb2Rv9niae+jTxCnJrWjzJ/Csgk6iaPQSqAtuB/wEX+r6f7OeSK5kX&#10;A+rTxDvYPi3qRWD7is/m/IZ95QXs6zMgNxcOOwLn/MvhhD9idhuSH8h56vc08dSniVeQZB7PNPvr&#10;wBW+71fzfb8G4BE9BrUz8MABxigihaQoJ3LYd3ymQkWcc3vhDJuIOb0DfPcN4di7CO8biP0iiLsd&#10;kdIinmTe2Pf9J3e88H1/GtDU9/3lQJmkRSYipZ6pXhPn0n44Q8ZA42aweiXhPQPIm3Av9nuNBkV2&#10;iCeZp3uel73jReznNM/zygEZSYtMRCTGZNYjrd8gnAHD4agsWLaIcPA1hFMmYH/VXbMi+1w0JuYW&#10;YIHneSuJkv8fgB7AUGB6EmMTEdmFycrGuXUkvLeI8IUnsfNnYxfNx3Q8F9P+HEzZcqkOUSQl9jsy&#10;931/NpBFdH38XqCh7/vzgGG+79+e5PhERHZhjME0bYEz9GFMj6uhTBnsjCmEt11N+MYcbF5eqkMU&#10;KXT7Teae5znAX4C/AbcC13qel+77/sZkBycisjcmPR2n9dk4wydiOneHzTnYyeMIh1yLXb5YhXFS&#10;qsRzzfweoA3wIHA/0XPIRyYzKBGReJlyFXC69cC5eyLmjI7wwzrCccMJR9yM/eyTVIcnUijiuWbe&#10;Efij7/vbADzPexn4ALg+mYGJiBwIU60GpldfbLuuhNOfhOWLCUfcDE2a45x3KaZO3VSHKJI08YzM&#10;nR2JHMD3/a3Atn3sLyKSMuawuqT1HYhz871w9LFRUh/cj/CpceSt/1+qwxNJinhG5u97nvcAMDb2&#10;+hrgw+SFJCJy8Mwxx+HcPALef4fwhSewC+fw7ZI3oF03zFnnYMpVSHWIIgkTz8j8GqA6sAj4D1AL&#10;uDaZQYmIJIIxBtOkOc6QsZiefTHlK2BnTSUceDXh/NnY7dtTHaJIQux3ZO77/q/A5fm3eZ7XCFif&#10;pJhERBLKpKVhWnWkzjndWffUBOyc6dgpE7Cvv4RzXi846bTfrfkuUpwU9BGo/0loFCIihcApXwGn&#10;c/fodrbWneCn7wknjCC8ZwB29YpUhydSYAVN5voKKyLFlqlSDadHH5yhD0PT02DNasKRA8kbOwy7&#10;7stUhydywOIpgNsTrcYgIsWeOTSTtD63YL8ICKc9Dh8sIfxwKaZlO0zXizHVaqY6RJG4FHRkLiJS&#10;YpgGLs5Nw3H6DYI6h2PffDVaHnb6U9ic31Idnsh+7XVk7nneRvY8AjeA7ukQkRLFGAONm+FkN8Uu&#10;mot9aQp29nPYhXMwnbtjWnXEpOtBkVI07WuaPXsf74mIlEgmLQ1zegdss1bY12dgX3kBO3USdu5M&#10;zLm9ME1bYBxNakrRstdk7vv+2sIMRESkKDFly2LO9rBndMS+/Cx2wb+xj4zE1p+Oc8HlmGNPSHWI&#10;Ijvp66WIyD6YylVwuvfGuWsc5uTTYe1nhKMGkTd6KPbr/6Y6PBGg4NXscfM87xTgXt/3W3uedxww&#10;MfbWp8BffN8Pkx2DiMjBMrXqYK4agO1wDuHzj8OKZYQr38Oc2gbTrQemRq1UhyilWFJH5p7nDQAm&#10;AWVjm+4GbvF9/3SiQrouyTy+iEiimSP/gHPjMJz+gyGzHnbRXMJBfyWc9gQ2Z1Oqw5NSKtkj88+A&#10;c4GnYq/P833fep5XBqgDbEjy8UVEEs4YA8c3xWl0InbxAuyLT2PnTMO++Sqm04WY1mdjMlT5LoUn&#10;qSNz3/enA9vzvbae59UDVgA1iZ6LLiJSLBknDee0tjjDxmPOvwzCEPvcvwhv/yvh4gXYUFcRpXAY&#10;a5O7mJvnefWBZ3zfP2237X8GTvd9//L9NKHV5kSkWMjbuIGNzz7GxpnPwvZtZBztUu2KaynXpHmq&#10;Q5PiKe6l05NeAJef53kzgBt93/8M2AjkxfO5devWJTSOzMzMhLdZ2qlPE099mniF0qedPJxmrbAz&#10;nmbbO2/w46B+cFwTnPMvw9RrkNxjp4B+TxMvMzPzgD9TqMkcuBd43PO8rUAO8JdCPr6ISNKZQw7F&#10;/PkGbPtuhNOegI+XE37yPuaUVphzemJq1k51iFLCJH2aPQGsRuZFn/o08dSniZeqPrUfL49uZ/tq&#10;DaSnY9p0jgrlKlYu9FgSTb+niZdvZB73NLsWjRERSTJzXBOcQQ9g/nw9VK2BffVFwoFXEc6Zhs3d&#10;murwpARQMhcRKQTGcXCat45WkrvwSsBgpz0RVb4vmosN4yohEtkjJXMRkUJkMsrgdDgHZ/gjmLPO&#10;g183YB8bTXjn37AfLaMYXPqUIkjJXEQkBUzFSjgXXI5z9wTMaW1h3ZeEY4YS3n87du1nqQ5Pihkl&#10;cxGRFDI1auFccR3OHQ9CdlNY9SHhsBsIHxmJ/fG7VIcnxURh35omIiJ7YOoeRdp1g7GffBCt8/7u&#10;m9j3/oM580+Ysy/CVK6S6hClCNPIXESkCDENG+MMvA/T+yaoXhM7dybhbVcRvuxjt6ryXfZMyVxE&#10;pIgxjoPT7Iyo8r17b0hLw744mXDQ1YRvvqrKd/kdJXMRkSLKpGfgtO2Cc/cjmE4XQs4m7JNjCYf0&#10;x37wrirfZSclcxGRIs5UqIhzbi+cYRMxLdvDd98Qjr2L8L6B2C+CVIcnRYCSuYhIMWGq18S57Fqc&#10;wWOgcTNYvZLwngHkTbgX+72WVC3NVM0uIlLMmMPrkdZvEHb1imjN92WLCN9/B3PGWZjO3TFVqqU6&#10;RClkGpmLiBRTJisb59aROH1uhpq1sfNnEw68mnDWVOzWLakOTwqRkrmISDFmjME0bYEz9GFMj6uh&#10;TBnsjCmEt11N+MYcbJ4q30sDJXMRkRLApKfjtD4bZ/hETOfusDkHO3kc4ZBrscsXq/K9hFMyFxEp&#10;QUy5CjjdeuDcPRFzRkf4YR3huOGEI27GfvZJqsOTJFEyFxEpgUy1Gji9+uIMGQtNmsPnqwhH3Eze&#10;uOHY775OdXiSYKpmFxEpwcxhdUnrOxD72cdR5fvyxYQfLMG07IDpejGmavVUhygJoJG5iEgpYI45&#10;DufmETh9B0Ltw7AL50RFcjOmYLfkpDo8OUhK5iIipYQxBtOkOc6QsZiefaFceeysqdHtbPNnY7dv&#10;T3WIUkBK5iIipYxJS8Np1RFn2ARMtx6Qm4udMoFwcD/ssrdV+V4MKZmLiJRSplx5nM7do9vZWneC&#10;n74nnDCC8N6/Y1evTHV4cgCUzEVESjlTpRpOjz44Qx+GpqfBFwHhyFvJGzsMu+7LVIcncVA1u4j8&#10;X3t3HiZVdeZx/Htu00AiLZsCaQQXIkQFFQloQGQTRlDiwuTggsHEgBqMJAZGRcAQkYQhLqBRwURx&#10;iZpXecDIJIhRUIwS1oBAkBAMRBkRZURZxG7unT9u9UynbaSrqYXb/fv8Q9Wtuue89T7089a599Q5&#10;IgC45sUUXHsz0aa3CGfNhFVLCFcvw519bjzzvVHTfIcoB6CRuYiI/At3QjuCUZMIrh8LLVoSLZof&#10;z3yf/TjRnt35Dk8qoZG5iIh8jnMOTutC0L4T0esvEf3uSaLfP0P06gu4CwbjepyHq1OY7zAlRSNz&#10;ERE5IFdQQNC9H8HE6biLhkBpCdHTDxGOH0G4dBFRGOY7REHFXEREqsDVq0dwvieYNAPXZyDs+IBo&#10;xhS23XgV0frV+Q6v1lMxFxGRKnNFDQkuHUZw+/24zt0p+ds6wjvHsn/qBKJ3/pHv8GqtrN8z996f&#10;CfzczHp5708HpgGlwD7g22a2PdsxiIhIZrmjW+CGj+aoK4ax7YEpsGY54doVuG/0xl14Oa7J0fkO&#10;sQISPlQAABDqSURBVFbJ6sjcez8aeAiolzp0DzDCzHoDs4Gbs9m/iIhkV90TTyb48USCG26D4tZE&#10;r79EOPY6wlmPEu3Zle/wao1sX2bfCFxc7vlgM3sz9bgOsDfL/YuISJY553AdOhGMvwd31UhocCTR&#10;vFnxmu/z5xCVlOQ7xBovq8XczGYTX1Ive74NwHvfFRgB3J3N/kVEJHdcUEDQrQ/BxAdwg4ZCGBI9&#10;8zDhuOsIFy/UzPcsctleUN97fyzwlJl1TT0fDNwCXGhmm6vQhFb8FxFJoP0ff8TH9gi7njcoLaGw&#10;TTsafecH1O94Vr5DSwpX1TfmdNEY7/0QYDjQ08w+qup5W7duzWgcxcXFGW+ztlNOM085zTzlNPMO&#10;mtMBgwm69CR67jeULF7I9rHXw8kdCQYNxbU+IXeBJkhxcXHa5+SsmHvvA2AqsBmY7b2PgFfMbEKu&#10;YhARkdxzRzXHXX0jUd8LCWc9CutWEv71L7gze+AuGoJr2izfISZe1ot56lJ619RTrdIvIlJLudZt&#10;KPjRT4nWrSR8dibR4oVEy17D9b4AN+BbuCOK8h1iYmnRGBERySl3ckeCsXfjrv4RNGxCNH8O4Zjh&#10;hPNmEX22L9/hJZKKuYiI5JwLAoKzesUryX3ru4AjmvVoPPP99ZeIwv35DjFRVMxFRCRvXGFdgn4X&#10;xWu+/9sl8PFOokemEv70h0RvLifbv7iqKVTMRUQk79wRDQj+/SqCOx7Ede0DW7cQTptAeNc4os0b&#10;8x3eYU/FXEREDhuuydEE3xlJMP4eaN8J1q8mnHgj4YwpRNvfy3d4h62c/s5cRESkKtwxx1Mw8jai&#10;v66K13lfuohoxRu4nv1x5w/GFR2Z7xAPKxqZi4jIYcuddBrBmF/gho2Cxk2JXnqe8NbhhP9lRPs0&#10;872MirmIiBzWXBAQdDknnvl+6TAoKCCa8wTh2GsIF83XzHdUzEVEJCFcnUKCPgMJ7piBG/At2LOL&#10;6LH7CH9yA9GqpbV65ruKuYiIJIr78hEEF19JMHE67uy+8N67hPfdTviLMUSb3sp3eHmhYi4iIonk&#10;GjclGPoDgtumwWldYMNawp+NJnxwMtG2z2/+4lyVNyFLHM1mFxGRRCtt1opNfUeys/EKvvL6byle&#10;/idKl7/BzlN702DwEDZtr8PLL7/LmjU7aN++Cb17t6Rt2yIKC2tOcVcxFxGRxCopiVi48D3Wr/+I&#10;yZPfJYq6MaDFO9zUbhXHr/4jJWsXsfTD05j659bs3V+HuXM3M3nySqZNO5uBA1vVmIKuy+wiIpJY&#10;GzZ8wubNu5g8eSXx/DfH799rRZ9XBzB2bSd27oErGy1hUY+5XNFqIwUuJIrghhteY8OGT/Idfsao&#10;mIuISGItWfI+W7bsouJE9tIo4LHNJ9J94QW8WtSTosJSftZhGfO7z6Nf83eIoogFC97NT9BZoMvs&#10;IiKSSM453n9/L1u27Drge3bvL+SJnZ15+IPjOXffq1x6zCZ+1ek1lu44ilfeLMS5k2vET9o0MhcR&#10;kUSKoohmzb5E69YNvvB9rVsXsf6/HWPWdKbvov7Me68lnZt8wKjwCUp/eQfRe+/kKOLs0chcREQS&#10;q0uXZuzfH+Ecn7vUDuAcFBcfwdatewD4++4jGb6iO50bb+fxS7bw5ZWLCVctwXXvhxt4Ga5h4xx/&#10;gszQyFxERBKrbdsijj22ATfd1JGKPyN3DqZM+QbPPvv3zx0fevsl1B87heD7Y6DZV4hemUd46zWE&#10;zz1J9OmeHH6CzNDIXEREEquw0NGzZwtat25Au3aNWLZsO2+//TGnnNKEc89tSZs2RZx6alMWLHiX&#10;NWv+h/btG9OrV7nfmXc8i+DUzkSvvUj0/FNEc58meuUP8Si9ez9cnWSUSZeAG//R1q2fX8nnUBQX&#10;F5PpNms75TTzlNPMU04z73DLadkqb5XVNufcF052iz7dS/Tic0QvzIZ9e6FZMcElV8IZXXO6elxx&#10;cXHZwyp3qsvsIiJSY0RRdMCCfbDBq6v/JYKBlxJMehDXawB8uI3wwcmEP/8Pog1rsxFuxqiYi4iI&#10;lOOObExw+bUEE34JnbrCprcIp9zC/vsmEm3dku/wKpWMmwEiIiI55poXU3DtzUSb3iKcNRNWLSFc&#10;vQx39rm4b16Ga9Q03yH+H43MRUREvoA7oR3BqEkE14+FFi2JFs2PZ77Pfpxoz+58hwdoZC4iInJQ&#10;zjk4rQtB+05Er79E9LsniX7/DNGrL+AuGIzrcR6uTmHe4tPIXEREpIpcQQFB934EE6fjLhoCpSVE&#10;Tz9EOH4E4dJFRGGYl7hUzEVERNLk6tUjON8TTJqB6zMQdnxANGMK4aRRROtX5zweFXMREZFqckUN&#10;CS4dRnD7/bjO3WHzRsI7x7J/6gSid/6RsziyXsy992d67xdUOHaX9354tvsWERHJBXd0C4Lhowlu&#10;vRPadYA1ywl/OpLwkalEO7Znvf+sToDz3o8GrgR2pZ4fBTwGnAisz2bfIiIiueaOO5HgxxNhzQrC&#10;WTPjyXJLF+H6DMT1H4T78hfv8FZd2R6ZbwQuLve8AXAb8HiW+xUREckL5xyuQyeC8ffgrhoJDY4k&#10;mjeLcMw1hPPnEJWUZLzPrBZzM5sNlJZ7/g8zW0oa682KiIgkkQsKCLr1IZj4AG7QUAhDomceJhx3&#10;HeHihRmd+a4JcCIiIlnk6tYjOG8QwaTpuL4Xws4dRL++i/COG4nWrcxIH7laNOaQRuLldpDJmGy0&#10;Wdspp5mnnGaecpp5ymlVFUPbcZRedjU7H3+APQv+QHj3bdQ/4ywaXvUD6rZpV+2Wc1XMK25Vk9a+&#10;q9oC9fCnnGaecpp5ymnmKafVdPl1BGf3I5z1KJ+uWMynK/+MO7MH7qIhtOxwetrNaT9zyQjlNPOU&#10;08xTTjNPOT100bqVhM/OhH++DXXqUDTwUhp974eg/cxFRESSwZ3ckWDs3birfwQNm/DJ7CfSbkMb&#10;rYiIiOSZCwLcWb2IOnWj4Yb0l4PVyFxEROQw4Qrr0qDvN9M+T8VcREQk4VTMRUREEk7FXEREJOFU&#10;zEVERBJOxVxERCThVMxFREQSTsVcREQk4VTMRUREEk7FXEREJOFUzEVERBJOxVxERCThVMxFREQS&#10;TsVcREQk4VTMRUREEk7FXEREJOFUzEVERBJOxVxERCThVMxFREQSTsVcREQk4VTMRUREEk7FXERE&#10;JOFUzEVERBJOxVxERCThVMxFREQSTsVcREQk4VTMRUREEk7FXEREJOHqZLsD7/2ZwM/NrJf3vg0w&#10;EwiBNWY2Itv9i4iI1HRZHZl770cDDwH1UofuAsaYWQ8g8N5fmM3+RUREaoNsX2bfCFxc7nknM1uU&#10;evwH4Nws9y8iIlLjZbWYm9lsoLTcIVfu8SdAw2z2LyIiUhtk/Z55BWG5x0XAR1U5qbi4OOOBZKPN&#10;2k45zTzlNPOU08xTTvMv18V8hff+HDN7FegPvFyFc9zB3yIiIlJ75bqYjwIe8t4XAn8Fns1x/yIi&#10;IjWOi6Io3zGIiIjIIdCiMSIiIgmnYi4iIpJwKuYiIiIJl+sJcHlRYUnZo4lXpWsEFADfNrO38xpg&#10;AlXI6enAA0AJsMHMvpff6JLHe18HeBg4DqgL3AGsQ8sfV9sBcroFuJd4/Yt9xH//2/MVY9JUllMz&#10;ez712uXA9WbWNX8RJs8B/p8uJs06VeNH5pUsKfufwBNm1hMYB3wtT6ElViU5HQ/8xMzOAep778/P&#10;W3DJNQT4IJXD84D70PLHh6qynN4DjDCz3sBs4OY8xpdE5XPanzineO87At/NZ2AJVllO065TNb6Y&#10;8/klZbsBx3jvXwQuBxbmI6iEq5jTlcBR3ntHvBhQSV6iSjYj/qOF+Jt4KXCGlj8+JBVzWgIMNrM3&#10;U8fqAHvzEViClc9pAJR475sAE4GReYsq2SrmtBToCrRKp07V+GJeyZKyxwE7zKwv8E/0zTxtleT0&#10;b8A0YC3QDH1BSpuZ7TGz3d77IuAZ4Fa0/PEhqSynZvY+gPe+KzACuDufMSZNJTkdB/wauBHYjRb5&#10;StsB/vaPBz5Mp07V+GJeiQ+B51OPnwc65TGWmmIq0M3MTgYeJ748LGny3rciXhXxUTN7mmoufyz/&#10;r0JOf5s6Nhi4HxhgZh/mM74kKp9T4qt0XyWeM/MUcJL3Xn//aarkb/8D0qxTtWICXAWLgAHAb4Bz&#10;iEeTcmg+JB45AmwlvkQkafDeNwdeIL6fuyB1eGU1lj+WlMpy6r0fAgwHepqZvhyl6QD/TzukXjsW&#10;eMrMbsxXfEl0gJy+Rpp1qjYW81HAr7z31wE7ie9HyKEZBvzWe18CfJZ6Lum5hXjm6jjv/XggIr4H&#10;ea+WP662ijktAE4BNgOzvfcR8IqZTchjjElT2f/T/ma2L79hJVplOR0K/DqdOqXlXEVERBKuNt4z&#10;FxERqVFUzEVERBJOxVxERCThVMxFREQSTsVcREQk4VTMRUREEq42/s5cJK+89wHwQ+Ay4t8+1wXm&#10;AuPN7LNqtPcI8KaZVWnlLe99H+AXxL9n/UoqhndSL/+MeLGKKreXZqw9gPvMrEOa54XAUWa2o8Lx&#10;HwPtzew7GQxTJHFUzEVy70HiddZ7m9kn3vsvAU8S70Q3NNudm9lLQEcA7/1tQFMzu6Hsde/9gCyH&#10;UJ3FLb7oHC2WIbWeirlIDnnvjyMekbcws90AZrbXe38N0DVV2N8FupjZxtQ584n34H459W834h3A&#10;5pjZ2Artn0S8zWcT4hH3NDObWY1Qu3nvBwHNgTXAZak4PwWeA04FrgD2EK/N/y/9ee+PAB4hXrc7&#10;BJab2TWptou8908Rb+tYDxhmZn/y3h8J/BI4PXXOPOAWMwtJbeCR2vv5XuId5LYB76M160V0z1wk&#10;x84A1pYV8jJm9r6ZzTGzvcBMUkvieu/bAG2JL8PfDtQzs3bEI+tu3vtzytrw3hcQ77p0k5l1BnoC&#10;o733XaoRZzHQO9X3McAlqeN1gefM7CRgFfESs5X1dzHQwMzOALqk4jsh1UZL4E4z6wjMAH6SOn4v&#10;8b7OHYCvA6cRL79c3gjiLwhfA/oBravx2URqHBVzkdwKOfjf3QPAlaniPAx4yMwioA/xdpOYWYmZ&#10;9UptwlKmLdAGeNh7vxJ4BahP6pJ6muaY2b7UqHgN8da2ZV6rQn+vAad47xcQb994j5ltSp33dzNb&#10;lnr8l3JtnwfcV/b5iG9H9E+9VnYpvQ/wpJntN7M9xBtRiNR6uswukltLiLeJPKL86Nx73xKYDgwy&#10;s79571cDFxFfyv566m2llLs/7L0/hvgyd5kC4H9So+Gy9zSjepehS8o9jvjXfap3Haw/M/vMe/9V&#10;4tF6b+Al7/31xDvsHajtil9yAqCwwrGKsZRW9QOJ1GQamYvkkJltJR5NPuy9LwIod694e7ndp+4H&#10;pgCLzWxb6tgfgaHee+e9r0d8ifuccs2/BXzqvb8i1W4r4lH1QfdCrqYD9ue9vxaYaWYvmtktxFs8&#10;tk+d5yptLbUNZKqtesRblc6vcM484Nve+3re+/rA4Ax/JpFEUjEXyb3vE29p+rr3fgXwBnERLL91&#10;7FygAfEl9zITiEe1q4DlwFwzm1P2YurS9IXA97z3q4gL361m9kaa8VWcHR5V9vgg/T0GBN77dd77&#10;pUAR8US5ytovcwPQ3Hv/ZuozrgcmVThnOvFnXwMsADZVbESkNtIWqCKHIe99V2B6ur/HFpHaSffM&#10;RQ4z3vuZQA/gyjyHIiIJoZG5iIhIwumeuYiISMKpmIuIiCScirmIiEjCqZiLiIgknIq5iIhIwqmY&#10;i4iIJNz/AuSj76YbXbeyAAAAAElFTkSuQmCC&#10;">
</div>
+
</div>
<div class="clear"></div>
+
<div class="clear"></div>
 +
 
 +
 +
</p><p class="c0"><span><b>pSB1C3 absolute quantification run #4</b><p>Lysate from 100,000 stationary phase cells harboring K909006-pSB1C3 was compared against a 2-point standard of 105 and 106 1.1x106 copies.  The 1.1x106-copy standard was created using lysate from 105 cells as well as 106 copies of purified plasmid.  This point was created to test for variance in amplification efficiency of plasmid vs. genomic template.  Linear regression indicates approximately 25.5 copies of the target sequence for every cell in the reaction, or around 24-25 plasmid copies per cell.
 +
 
 +
Three qPCR runs using stationary phase cells and one run using mid-log phase cells indicate a PCN of around 12-13 copies during log growth, increasing to around 24 copies per cell during stationary phase.
 +
</p></p>
 +
<div class="img-block">
 +
<!-- fig4 -->
 +
<img src="https://static.igem.org/mediawiki/2016/f/f4/T--genspace--pSB1C3_Absolute_Quantification_4.png" alt="">
 +
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAe4AAAGMCAYAAAAcK0EHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz&#10;AAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd4FVX+x/H3mST0jhQjVTEjEkBQQEBFeldRGewVXVZ2&#10;YdVdRVfXXtBVVyxYsK0FGbAtRSkSihQBASnqxIJYsCMCAlLm/P6YG36hXyA3N5d8Xs/DQ+7cuTPf&#10;GUI+OWfOnDHWWkRERCQ1OMkuQEREROKn4BYREUkhCm4REZEUouAWERFJIQpuERGRFKLgFhERSSEK&#10;bhERkRSSnuwCRAqT67qnANOAJ4IguCrf8ouBfwdBUC0B+2wH5ADlgiDYEMf6jYGqQRBMO4h9VgCu&#10;B84GagPfA+OAu4Mg+P5At3sAdRwGdA6CYGTsdQ4wPwiC61zXNcBzQF/gR+BW4P4gCKoXwH53OIeu&#10;64ZAryAIJhzstvex3y7AO0C9IAi+SuS+pPhSi1uKm/OBXOAc13VL7vReImcj2p9tvwUce6A7ioXl&#10;+0A74CrABS6N/b3Add2jDnTbB+A+oE++132A22JftwYuii1rC7zKQRz3TnY+hzWByQW07d1yXbcc&#10;8DSJ/T4SUYtbig/XdUsQtUD/BjwJnAW8ktSids8c5Of/A6wB2gVBsC227GvXdWcQtQafAU49yH3E&#10;a4djCYJgTb6XlQEbBMGkfMv+SNB+fyyg7e7NA8AXQK1C2JcUY0ZTnkpx4brumcAooAbwIlAyCIJO&#10;sfcuBu4HHgKujX3kv8DfgyAIXddNIwrEs4GKwAfANUEQzI99/ijg30St3BB4Pfb++lhX+VSgPFAN&#10;WAFkB0HwUb59/zsIgmqxruR2RK226UEQdHBdtwbwCNANWA+MB64NgmDtbo6xMlG3eJ/ddQu7rnsi&#10;MBtoFATBx67rriDqnn489n7d/PW5rls9dk46x477a+CuIAiei62fA0wHjgO6AD8DtwZB8KzrurcA&#10;t8R2bYMgSMvrKgeWE3WTEzvW24CV5Ltc4bpuE6IwPBFYDQwPguDe2HstgHuAVkQNkA+BQUEQzNvD&#10;OdzeVe66bgZwI3AxcDiwIHY+5+3lmG4LguCZnc9nvvPameiXwXOBOairXBJIXeVSnJwPzAqCYDVR&#10;sJ4aC6o8hxH9oD41tu55wHWx9/4K9AZOI+qCzQVGA7iuWwl4j6i12Jao6/ckopbt7uzut+W8ZWcC&#10;3xAFy5mxZW8A24hCqhdwJFG38u4cTxRkc3b3ZhAEc4FNQJs9fH7n+l4kOi/tgYZEXdDDXdfNPxbg&#10;OmAC0Xl5A3g89v6/AR8YS9RVnd+rwIWxfdWMrbt9367rVgXeJToXJwBXAkNc170k1iU9AVgINCY6&#10;L+uJghN2fw7zexS4DPgzUTgvBybHfkHa0zE9ttMxbxer56lYjetRV7kkmIJbigXXdSsCPYDXYove&#10;JGoZX5Jvta3AeUEQLAuCYCJwJ9E1YoB6RIH3dRAEXwLXABfHBlhdQPR/6aIgCD4OgmBmbLt993A9&#10;eY9d4UEQ/EoU0uuCIFjjum57IBu4MLbthUSB18113Ya72cRhsb/X7WkfRK3Xw/byfv76xgJ/CoJg&#10;eRAEXwB3AyWArHzr5ARB8FTsvNwUe79pEAS/AxuBP4Ig+Gmn4/yDqDufIAh+2s2gvXOAzcAVQWQi&#10;UdCuB8oAQ4EhQRB8GQTBEmA40Xna5Rzm32js++Ay4G9BEEwMgiCIbfdr4C/7OqY9nK9/A+8GQTBl&#10;D++LFCgFtxQX/Yh++L4BEATBL0TdoRfnW+fbIAi+y/f6A+CI2Ajt4UA5omvFM4E/AR8FQWCJWqKL&#10;gyDYnO+z84mCp9FB1n0sUBb41XXdda7rrgMCol86jtnN+r/E/t7bddaKxEIzDsOBE13XHea67jvA&#10;R0QtyrR863ya90UQBHm/MGTEuf09aQgsCYJga75tjwyCYEzsevUIYKDruiNi1+5fIL6fZ1mx9ebm&#10;264ldvkg33pxHZPrup2IekGuiS062PEJIvukwWlSXJwf+3uF67p5ywxgXNftGHu9bafP5AXBliAI&#10;Atd16wNdge7AIOAvruu2ImqJ745hx4CD3Xej7u3/YTrwJdCJXUPhh92sv4Co56Bl7HM7cF33eKJf&#10;BObvoZ70fOsaYCKQSdS1PZWoWznY6TOb2dXBBtjmPW3Ddd3DgXnAJ8DbsdqqAS/Fsd1Ne9iuw47/&#10;VvEe03mxfX8b+75yYustd133rrxr8iIFSS1uOeS5rluH6JrzLUTdnXl/jifqer0stmqt2PXqPG2A&#10;lUEQbHRd9wKgXxAE44IgGEh0a1X12HY/Bo7b6faylkQh+PFO5eQFQvl8y3buTs8fph8TBef6IAi+&#10;iHVXbyMaKLfL/c6xbmIfuCU2CAvXddu6rrvEdd1ewB3AB7Eu97x6dq4lb//NgA5A9yAIbg+C4E2i&#10;keAQfzAf6PXeXCA7NiiQ2HH8y3XdUUQDwLYEQdA5CIIHY13UtePc72fAFna9xt+aqDdhf11H1DuQ&#10;9z11Vmzf3YEnDmB7IvukFrcUBxcQXWsdtvNIbNd1XwD6E7VA04GRruteTxRgNxBNYgJQAbjddd1f&#10;iH7A9yIKr4XAKuBfwH9d170dqAo8DkwOguCT2KCnvKD7geh66rWu6w4h+mF/yU71rgcaxgZDTY7t&#10;b5Trun8n6iJ/lKjb/ss9HO/fiC4D5LiuexvwOTAL+B9RqOQPrfnARbFu8FJEwZ4Xet8Tu+7vuu7L&#10;RL+sPBx7f+d74PdkPdDIdd26QRCsjPMzAC8TTcjyuOu6DwANYsc1mOiXjRqu6/YElhENnPsnRLf8&#10;xS5ZbD+H+a+vx34JewR40HXd34lG0A8G6hLdg71fgiD4mWjUObH9lyb6t/5q5+vrIgVFLW4pDs4D&#10;Xt3d7VNEIViCaET4R0RBNoPo2u6/gyB4GiB2u9SjseWfEI0gPjsIgs+DINhINBq9IlEX7mii2dnO&#10;yrcfG9uOJQrqhkTdzoOJfkHI72GiXzbeia1/GtG166mxP6uAHrH3dhG7ft86VsOjROHWi+j2tteB&#10;V2Otb4gC71uiUejPE/VKhLHtrIod5xVELf//AI8BS4h6K/Ykf13PE91ytTx2a1lcYteVuxNdx18c&#10;2+9tQRC8SNSj8DTR7WQfxurrH9tvXl3bz+FuarqB6LbA54jGMTQETo31Zuy87u6OaV80qlwSKuH3&#10;cXue1wq41/f99p7nVSP6D1eJ6HrSRb7vr0hoASKyg9i0nFuCIMhJdi0isv8S2uL2PO8fREGd1612&#10;H/CS7/unAjez+1GxIpJAQRBMUmiLpK5Ed5V/xo7zFLcFanmeN5mo+3JagvcvIiJySElocPu+/wbR&#10;4JY89YDVvu93JhqgMySR+xcRETnUFPao8l+IZmIi9vedcXxGAz1ERKQ42u1tl4Ud3DOJpp18GTiF&#10;aFTtPq1atSqRNRU5mZmZxe6Yd6ZzoHNQ3I8fdA6g+J6DzMzMPb5X2MH9d2CE53l/Bn4jus4tIiIi&#10;cUp4cPu+v5LYhA++739FdL+riIiIHABNwCIiIpJCFNwiIiIpRMEtIiKSQhTcIiIiKUTBLSIikkL0&#10;WE8REUkJixcv5vbbb6devXoA/P7772RmZnLTTTeRlrb90e1Yaxk+fDgrVqxg8+bNlC5dmsGDB3P4&#10;4Yfvcx+bN2/mrrvuYs2aNZQpU4YhQ4ZQsWLFHdYZOXIkU6dOpWzZsvTr14/WrVszcuRI5s2bhzGG&#10;devW8euvvzJmzBgAtm3bxh133EHPnj1p0aLFQZ8HtbhFRCRlNGvWjAcffJAHH3yQJ598krS0NGbN&#10;mrXDOvPmzeOXX37h/vvv5+GHH6Z37948/vjjcW3/rbfe4sgjj+Thhx+mc+fOvPjiizu8v2LFCqZO&#10;ncrw4cO57777eO6559i8eTPnnnsuDz30EA8++CDVqlXjhhuip/WuWrWKv/3tbwRBUDAnALW4RUQk&#10;RW3ZsoXVq1dTvnz5HZZXqlSJ3NxccnJyaN68OW3btuXEE08EYPr06bz00ktUqlSJsmXL0rp1a7p2&#10;7br9s0uXLuXcc88FoFWrVrsE98qVKznuuONIT4/is1atWnz++ec0bNgQgBkzZlC+fHmOPz56NPym&#10;TZv4xz/+wciRIwvsuBXcIiKy38LRz2E/mLXvFfeDOb4tTt9L97rOokWLuOaaa1i9ejWO49C7d2+a&#10;NWu2wzqu63LttdcyduxYHnnkEapXr85VV11Fo0aNGD58OCNGjKBs2bIMGbLrc642bNhA2bJlAShT&#10;pgwbNmzY4f0jjzySV155hY0bN7J582aWL19O7969t78/cuRIbr755h3WL2gKbhERSRnNmjXj5ptv&#10;Zu3atfzjH/+gZs2au6zzxRdfULt27e0BumDBAm699VaeeeYZKlSoQLly5QBo2rTpLp8tU6YMGzdu&#10;BKIQz1s3T506dTjjjDO4/vrrqV69Og0bNtx+DXzlypWUK1dur/OMFwQFt4iI7Den76Wwj9ZxIlWo&#10;UIEbb7yRq6++mhEjRlClSpXt733wwQesXLmSa6+9FmMMdevWpXTp0lSuXJlNmzaxZs0aKlWqRBAE&#10;tGnTZoftZmdnM3fuXFzX5f3336dx48Y7vP/bb7+xYcMGhg0bxu+//851111H/fr1t++3VatWCT92&#10;BbeIiKSkunXrctZZZ/HII49wyy23bF9+5pln8sQTT9C/f3/KlSuHMYZ//vOfAFx99dXceOONlC1b&#10;lj/++GOXbZ5++uncc889DBo0iIyMDG666SYARo8eTa1atWjdujVfffUVf/7zn8nIyGDAgAEYEz19&#10;85tvvtl+bTuRjLVF/nHXtrg90q24PsYuP50DnYPifvygcwCJPQdPP/00derU2WFwWlER627f7fO4&#10;dTuYiIhIClFXuYiIFEtXXHFFsks4IGpxi4iIpBAFt4iISApRcIuIiKQQBbeIiCSEtbBhwza2bi3y&#10;dy+lFAW3iIgUqG3bLMuXr+Wuuz7ktNMmcd55OUycuIqff95c4Pt64403DnobAwcO5Icfftjvz331&#10;1VdcffXVB73//aVR5SIiUqBmzPiRiy+eyrZt/9/SnjXrezp3rsV997WievWSBbavl156iT59+hTY&#10;9vZX3uQrhUnBLSIiBeabbzYyYMCMHUI7z+TJ3zB7dn3OOKP2AW77G4YOHUp6ejphGNK8eXPWrVvH&#10;ww8/zBVXXMH999/P77//zi+//MLpp5/OaaedxtVXX02DBg1YsWIFGzZs4NZbb6V69eqMGDGCBQsW&#10;UK1aNdauXQvATz/9xH/+8x82b97M6tWrueyyy2jbti2XXXYZtWrVIiMjg4EDB3LnnXcCULly5e21&#10;jRgxgsWLFxOGIaeccgrnnHPOAR1jPBTcIiJSYHJzf2P9+i17fP+RR5bSqVMm5cql7fe2FyxYQMOG&#10;DfnTn/7E0qVLqVixImPHjmXw4MF8+umndOzYkZNOOolffvmFq6++mtNOOw2Ahg0bMnDgQJ555hne&#10;ffddmjdvztKlS3niiSfYsGEDF154IRB1fXueR9OmTVm+fDnPP/88bdu2ZePGjVx88cUcddRRDBs2&#10;jI4dO9KzZ09ycnIYO3YsAFOnTuWhhx6iSpUqTJw48QDOXPwU3CIiUmDWrdtzaAP88MNGNm3adkDB&#10;3aNHD0aOHMl1111HuXLluPzyy7e/V7lyZcaMGcOMGTMoU6YMW7du3f5egwYNAKhWrRq//vor33zz&#10;Da7rAtHTwPIeElK1alVefPFFJkyYAMC2bdu2b6N27aiX4Ouvv6ZXr15A9ECSvOC+8cYbeeqpp/j1&#10;119p2bLlfh/b/tDgNBERKTDVq5fe6/tNmlSlXLkDazPOmjWLJk2a8MADD9CuXTtGjhxJ3vM2fN+n&#10;UaNG3HjjjZx66qnkfw7Hzteh69atyyeffALAxo0bWblyJQDPPvssXbt25YYbbqBZs2a73Ua9evVY&#10;tmwZwPZtbN26lenTp3PzzTfz4IMP8s477/Djjz8e0DHGQy1uEREpMFlZFahbtxwrV67f7ftXXdWI&#10;UqUOrM3oui733nsvL774Itba7aPB7777bnr06MGwYcPIycmhbNmypKens2XLlt0OHmvQoAEtW7Zk&#10;wIABVK1adfu16lNPPZXhw4fzyiuvcNhhh22/9p1/GxdccAF33XUX06ZN2/4s8PT0dMqXL89VV11F&#10;qVKlaNGiBdWrVz+gY4yHng5WBOmJQDoHoHNQ3I8fUvccBME6zj//Xb77bsP2ZcbALbecwPnnH0WZ&#10;MvF3k6fqOThYe3s6mFrcIiJSoFy3POPGdefjj9fwySe/UrlyKY47ripHHlmWEiV0hfZgKbhFRKTA&#10;1axZkpo1a9C+fY1kl3LI0a8+IiIiKUTBLSIikkIU3CIiIilEwS0iIglhrCV9wwacfJOhyMFTcIuI&#10;SIEy27ZRZvlyKt11F1VPO42q551HuYkTKfHzzwe13c2bNzN+/Pj9+sySJUtYsWLFQe23qFFwi4hI&#10;gSo7YwYVu3en9PDhpH38MRmzZlHhssuo8Pe/U+IgZhRbvXr19ulI4/X222/z008/HfA+iyLdDiYi&#10;IgWm5DffUH7AAEy+eb7zlJg8mZKzZ7P5jDMOaNsvvfQSK1eu5IUXXmDFihXbZzb761//Sv369Rk6&#10;dCirVq1i8+bNnHnmmdStW5d58+bx6aefUr9+fapVq3ZQx1ZUKLhFRKTAZOTmYtbvfrpTgNKPPMLG&#10;Tp3YWq7cfm/7ggsuYMWKFWzevJnmzZtz2mmn8e233zJ06FCGDh3K0qVLeeyxxwD44IMPyMrKomXL&#10;lnTo0OGQCW1QcIuISAEy69bt9X3nhx9wNm2CAwjuPF988QULFy5k2rRpWGtZt24dpUuXZuDAgTzw&#10;wANs2LCBTp06HfD2izoFt4iIFJhwHw/X2NqkCdsOMLQdxyEMQ+rUqUPnzp3p0KEDa9asYcKECaxe&#10;vZrc3Fxuv/12Nm/ezDnnnEOXLl0wxhCG4QHtr6hScIuISIHZkpXF1rp1SY89KnNnm666im2lSh3Q&#10;titVqsS2bdvYsGED06ZNY+zYsWzYsIFLLrmEKlWqsHr1av7yl7+QlpZGv379cByHhg0b8vTTT3P4&#10;4YdTp06dgzm0IkNPByuCiuvTcPLTOdA5KO7HD6l7DkoHARXPPx/nu++2L7PGsOGWW1h//vlsK1Mm&#10;7m2l6jk4WHo6mIiIFJqNrsu2ceMo8fHHpH3yCbZyZbYcdxx/HHkkYYkSyS4v5Sm4RUSkwG2uWZPN&#10;NWtC+/bJLuWQowlYREREUoiCW0REJIUouEVERFKIgltERCSFJHxwmud5rYB7fd9v73neccA4IDf2&#10;9nDf90cnugYREZFDRUKD2/O8fwAXAnkT1x4PPOD7/kOJ3K+IiMihKtEt7s+APsCLsdfHA1me550B&#10;fAoM9n3/9wTXICIicshI6DVu3/ffALbmW/Q+8A/f99sBXwC3JnL/IiIih5rCHpz2pu/7i2JfvwEc&#10;V8j7FxERSWmFPXPaRM/z/uL7/gKgI/BBPB+KzdlarBTHY96ZzoHOQXE/ftA5AJ2DnRV2cP8ZeMTz&#10;vM3A98CV8XyouE0wX1wn1c9P50DnoLgfP+gcQPE9B3v7ZSXhwe37/kqgTezrRcBJid6niIjIoUoT&#10;sIiIiKQQBbeIiEgKUXCLiIikEAW3iIhIClFwi4iIpBAFt4iISApRcIuIiKQQBbeIiEgKUXCLiIik&#10;EAW3iIhIClFwi4iIpBAFt4iISApRcIuIiKQQBbeIiEgKUXCLiIikEAW3iIhIClFwi4iIpBAFt4iI&#10;SApJieAOp7+D3bJlt+8ZYwq5GhERkeRJT3YB8bAvPY4d72O6nok5uTOOcSiVm0uJqVNJX7aMrdnZ&#10;bO7QgU1ZWdiMjGSXKyIikjApEdymyxnYaW9jX30KO8GnRGYDKgwbQdrWbQCUHDeOMkOHsn7YMNb3&#10;7q3wFhGRQ1ZKdJU7fS/DuXcEpvvZsGkjmz5ZwPftGrH2qJqE6dEhGGspN2gQpXJzk1ytiIhI4qRE&#10;cAOY8hVxzryISg1aU+HTVVjH8Jt7BN+d2pjfGhxOmJ6GsZYSOTnJLlVERCRhUqKrPI8xhhKfBJT8&#10;9DvKr/iB9XWrs65eddZmZbKufg3KrfyRkks/xBiDtTbZ5YqIiBS4lGlxA1hr2ZqdDYCzNaTC599z&#10;+LRlVPz4a0wYsq7B4fzMT2zzn8H+9muSqxURESl4KRXcAJs7dMDmuwXM2RZSYcWPHJ6zlEoffY0p&#10;Uw476U3CG64gHPkUdvXPSaxWRESkYKVccG/KymL9sGE7hDeAscDf/4Vz11OYC66CCpWwU8cR3ngl&#10;4YuPYX/6PjkFi4iIFKCUusYNYDMyWN+7N1tdlxI5Of9/H3f79mzKyoKMDJx23bBtO2Hfn46dMBo7&#10;YyL2vcmYE9tjevTF1MhM9mGIiIgckJQLbojCe2OjRmxs1GiPA9FMejqmbUfsiadiF7yHHe9jZ7+L&#10;nZODaXEypmdfTGadJFQvIiJy4FIyuPPb1+hxk5aGadUO2+JkWDSHcJyPnTcdO38GNG+N07Mfpnb9&#10;QqpWRETk4KR8cMfLOA4c3xaneRtYMp9w3Cj4YDbhB7OhacsowOsfnewyRURE9qrYBHceY0wU1E1a&#10;wPJFhONHwYfzCD+cB42a4fTqh2lwbLLLFBER2a1iF9x5jDGQ3RynUTMIlkYt8OWLCJcvArcxTq9+&#10;4DbW08dERKRIKbbBnccYA8c0Ie2YJtjPPvr/AA+WQoOGOD37QaNmCnARESkSin1w52caHEva327D&#10;rsglHO9HXegP3wr1jo5a4E1aKMBFRCSpFNy7YepnkfaXm7BffUE4wYeFcwgfvRNq1cfp5UGz1tFg&#10;NxERkUKm4N4LU+dI0gYMwa76Cjt+NHb+TMInhsLhtTE9PUyLkzBOWrLLFBGRYkTNxjiYzDo4V1yL&#10;c8fjmDYd4YdvsSMeILx5IOGsd7Fbtya7RBERKSYU3PvB1MjEuXQwzp1PYE7pCr/8iH3+YcKbBhBO&#10;fwe7ZUuySxQRkUOcgvsAmGo1cS4ciHP3U5gOvWDtGuxLjxP+80+E747Dbv4j2SWKiMghSsF9EEyV&#10;w3DOvRLnnqcxXc6A39dhX30qeiLZpDewf2xKdokiInKIUXAXAFOxMk7fy3DuHYHpfjb8sQk7+jnC&#10;If0JJ4zGbtyQ7BJFROQQoeAuQKZ8RZwzL8K59xlM73Mh3IZ940XCIZcT/u8V7O/rk12iiIikOAV3&#10;Apiy5XBOOzcK8D4XgpOGHftqFOCv/xe77rdklygiIilKwZ1ApnQZnB59oy70vpdCiZLYt8dEXeij&#10;n8WuWZ3sEkVEJMVoApZCYEqWwnTpgz21B3bmZOw7r2EnvYmdOh5zchdMtzMxVaolu0wREUkBCu5C&#10;ZEqUxHTshT2lK3bOu9gJY7A547EzJmLadsR0OwtTrWayyxQRkSJMwZ0EJiMDc0o3bJtO2PenYyeM&#10;xs6YiH1vMubE9my5ZCAY/dOIiMiuEn6N2/O8Vp7n5ey07DzP82Ynet9FnUlPx2nbEeeOxzD9r4Ua&#10;R2Bnv8v3A84mfPoB7Kqvkl2iiIgUMQlt1nme9w/gQmB9vmXNgMsSud9UY5w0TKt22BYnw6I5pE18&#10;gy3zpmPnz4BmrXF6epg6Rya7TBERKQIS3eL+DOiT98LzvKrAncDgBO83JRnHwRzflhqPvIzzl5ug&#10;bgNYOJvwjr+x7dE7sSs+TXaJIiKSZAltcfu+/4bneXUBPM9zgBHANcAfgEnkvlOZMQbTtCVOkxaw&#10;fBHh+FHw4TzCD+dBo2Y4vfphGhyb7DJFRCQJCnMEVHOgATAcKA009DzvQd/3rynEGlKKMQaym+M0&#10;agbBUsJxo6IgX74I3MY4vfqB2zhaT0REigVjrU3oDmIt7ld932+907KRvu+3iWMTiS2wiAvDkDAM&#10;cRwHx3H446PFrH31WTZ9EI3tK3FsUyr0u5xSx7cuEgGeV2+evLpFRGS/7faHemG1uA8qfFetWlVQ&#10;daSEzMxMVq78ltzcdUyd+i3Llq0mO7sKHTocQVZWNTIGDMFZ8Snh+FFs/nAeP98yCOodjdPTg6Yt&#10;kxLgW7ZYcnPXsXjxz5Qpk0Fu7ho++2wtTZrk1V2ejIz468rMzCx2/+47K+7noLgfP+gcQPE9B5mZ&#10;mXt8L+Et7gJgi9s/WqVKVXn22UUMGvQe+f95jIFhw06id+/a20PQfr0iuga+cA5YC7Xq4/TyoFlr&#10;TCG1dLdssYwd+zVPPvkRvXrVZejQRfuse1+K63/W/Ir7OSjuxw86B1B8z0EsuHf7A1N9mEXQggXf&#10;7hLaEOXyoEHvkZu7bvsyU7s+aQOG4Nz6CKZlO/h2JeETQwlv/Svh3GnYbdsSXm9u7joGDXqPvn2P&#10;2iW091S3iIgcGAV3ETRx4spdwi+PtZCT8+0uy01mHZwrrsW543FM247w4yrsMw8S/usqwllTsFu3&#10;JqzeqVO/5fDDy/DVV+v3u24REdk/Cu4ixhjDkiU/73WdZct+3e11bGMMTs0jcC4ZjHPnE5hTusEv&#10;P2GfH0Z40wDC6e9gt2zZYf2CqHfZstXUrBkF94HULSIi8dOE2EWMtZYmTQ5j3LiVe1wnO7syeWMT&#10;tmyxBMFaJk/+luXLV1O/fnlatKhO3brlOPKcP5Pe08NOfB07cxL2pccJx43ix+N68ubPWXz40bp8&#10;g972b/BY/nqzs6uwcOFPNGu29yec5a9bREQOzD5b3J7nNS+MQuT/de1alz01TI2B9u2PAKLQ/t//&#10;vqZbt/H8+9+Lefvtr3j88eVcdlkOkyZ9w7Rp37O1fFWcc6/EuedpbKcz2LZuHTWm/Zc+H9xJ5vKJ&#10;DLt/Hl27jmPs2K/ZsuXAQrVDhyP47rsN1KlTLq66RUTkwMXTVf5ywquQHZxwwhEMG3bSLiFoDDzy&#10;yMlkZZUHokFhgwfvfhDb0KGL+PLL9dsHhJmKlQmyz+aEiT155LNjKe1s5aaGi5ndfixXHbmcG6/J&#10;OeDBY1lZ5Rk27CRGj/6c669vts+6RUTkwMXTVb7E87zzgPfI97AQ3/dXJ6yqYq5MmZL07l0b1+1F&#10;Ts63LFtRZVXSAAAgAElEQVT2K9nZlWnffscu7alTv93rYLCvv17P/PmGRo0qbF9/9eaS3J/bhKe+&#10;OIZL6+Vyef2A692lDDjyE3JH/oa94TJM2XL7VW9GhonVW4kPP/yZRx45mU8//Y3PP//toLviRURk&#10;R/EE9+lA352WWSCt4MuRPBkZUeA2alQBY8wu14bzBoXtzddfr6ds2fTtA8Lyr//b1hL857NsRnzp&#10;cnHdT+lfL6DFD1MIh8zCtO+B6XwGpnzFg6p3d3WLiMjB2Wdw+75fqjAKkT3bXfjlDQrb2yC22rXL&#10;UaNG6e2f393667dm8Njnx/Lsl1k8d8lG2vw+C/v2a9h3x2HadcN06YOpVOWA6lVoi4gUvH0Gd+yp&#10;XtcA2cBfgb8A9/m+n/iZPWSvOnQ4YrcTnkB0Xbl27XK0aFE9rvU3helU6XcuztGXYN+bjH3ndezk&#10;t7A5EzAnd8F0OxNTZe+jxkVEJPHiGZx2P9AEaBVbvxvwUCKLkvhkZZXn4Yd3P4htyJDm1KtXfocB&#10;YXmDyPY2eMyUKInToRfOXU9iLrwKKlbG5ownvPFPhC8+hv3p+0I4MhER2ZN4rnF3JHok5we+7//m&#10;eV4XYHFiy5J4ZGQYTjutNq7bkylTovu469WrwAknVKNevXIceWS5HQaE/f8gsr0PegMwGRmYU7ph&#10;23TCvj8dO2E0dsZE7HuTMSe2x3Q/G1NTt3eJiBS2eIJ7i+/7oed5APi+/4fneYmbP1P2S0aGITu7&#10;ItnZFbcPQtvbteV9DXrbmUlPx7TtiG19Knb+e9jxPnb2u9g5OZgWJ2F6eJgj6hToMYmIyJ7FE9zL&#10;PM8bCKR5nucSXe9Wi7sI2t/BYPuzvnHSMK3aYVucDIvmEo4bhZ03AztvBjRvg9PTw9Q5cn9LFhGR&#10;/RRPcA8muqZdA5gFTAQGJbIoKbqM48DxbXCat4Yl8wnHjYKFswkXzoamLaMAr5+V7DJFRA5Z8dwO&#10;tha4vBBqkRRijImCukkLWL4oeib4h/MIP5wHxzbD6dUPc/SxyS5TROSQE8/tYNWBh4HOwBZgAnCt&#10;7/trElybpABjDGQ3x2nUDHKXRS3wjxYRfrQI3MY4PT04pomeCiYiUkDi6Sp/GlgGtCS6HWwA8CTQ&#10;L4F1SYoxxoDbmDS3Mfazj6MW+LKFhMFSOOoYnF79oFFzBbiIyEGKJ7jr+b5/er7Xf/c8b2miCpLU&#10;Zxo0JG3wrdgVn/5/F/rDt0HdBlGAN22pABcROUDxTMCyyvO8+nkvPM+rBXyXuJLkUGHqH03aX27C&#10;+dfDcHwb+OpzwsfuIrx9MHbBe9gwTHaJIiIpZ48tbs/zxhI9TKQasNjzvCnANqA9sKRwypNDgald&#10;n7QBQ7Crvoomcpk3k/DJ++Dw2pgefTEtTsak6Zk1IiLx2FtX+Zg9LB+fiELk0Gcy62D6X4vtfS72&#10;7dHYudOwzzyIHTsyCvBWp2LS47l6IyJSfO3xp6Tv+y/kf+15XpnElyPFgamRiblkMLbXOdGTyGZP&#10;wT4/DDv2VUy3szBtOyW7RBGRIiue28GuBu4CSsYWGfQ8bikA5rAamAuvwvb0sBNfx86chH15OHa8&#10;z7p+l2KbtMKUKLnvDYmIFCPx9EteA5wIfJ7gWqSYMlUOw5x7JbZHX+ykN7HTJrDmyX9DhUrR88Db&#10;dcOUKp3sMkVEioR4gvtT3/c1GE0SzlSsjOl7KbbbWZSd+y7r/vcqdsxz2HfGYDqdjmnfE1OmbLLL&#10;FBFJqniC+1HP80YBk4hmTgPA9/3/JqwqKdZM+QpUunggv7fpjH13LPbd/2HffAk76Q1Mh96YTr0x&#10;Zcvve0MiIoegeIJ7INEDRvIPTrOAglsSypQthzntXGzn07HTJkTd6ONexU55C9O+B6bzGZjyFZNd&#10;pohIoYonuOv4vn90wisR2QNTugym+9nYDr2w09/BTnojGo3+7rjo+neXPphKVZJdpohIoYhn5rQv&#10;Pc/LTHglIvtgSpbC6XIGzt1PYc69EsqWx05+i/CGKwhfeRK7+qdklygiknDxtLg3Ass8z5sP/JG3&#10;0Pf90xJWlchemBIlMR16YU/uip3zLnbCGGzOeOyMiZg2HTDdz8ZUq5nsMkVEEiKe4H4t9kekSDEZ&#10;GZhTumHbdMLOm44dPzq6F3zWlGgWth59MTWPSHaZIiIFap/BvfMMaiJFjUlPx7TpiD3xVOz897Dj&#10;feycqdi50zAtTsL08DBH1El2mSIiBSKemdPWEY0i34Hv+xUSUpHIATJOGqZVO2yLk2HRXMLxo7Dz&#10;ZmDnzYDmrXF6epg6RyW7TBGRgxJPV3l2vq9LAGcSPSVMpEgyjgPHt8Fp3hqWLIieCb5wDuHCOdCk&#10;BU6vfpj6WckuU0TkgMTTVb5yp0VDPc97H/h3YkoSKRjGGGjaAqfJCfDRYsJxo2DJfMIl8+HYZlGA&#10;H31ssssUEdkv+/0MRc/zjiGakEUkJRhjoFEznGOPg9xlUYB/tIjwo0XgNsbp6cExTaL1RESKuP29&#10;xm2IusuvS2RRIolgjAG3MWluY+xnH0dd6MsWEgZL4ahjcHr2g+zmCnARKdL29xq3Bdb4vr82QfWI&#10;FArToCFpg2/FrviUcIIPi98nHHYb1G2A08uDpq0U4CJSJO0xuD3Py7t/ZucR5ZU8z6vk+/5XiStL&#10;pHCY+keTNvCf2K9XRLeRLZxN+NjdUKte1IXevE002E1EpIjYW4t7OVFo5292WKA00VSpaQmsS6RQ&#10;mdr1MQOux676CjthNHbeTMIn74PDa2N6nI1pcQomTd/yIpJ8ewxu3/d3eG6i53kGuBH4e+yPyCHH&#10;ZNbB9L8W2/tc7NujsXOnYZ95CDv21Wgq1RPbY9L3e0yniEiBiasP0PO8I4CpQB+gle/7zyS0KpEk&#10;MzUycS4ZjHPnE5hTusHqn7AvPEJ40wDCaW9jt2zZ90ZERBJgn8Hted6ZwIfAB0Br3/dzE16VSBFh&#10;DquBc+FVOHc9henYG9auwb48nPDGKwnfHYvd/Me+NyIiUoD2NjitNPAw0BM4x/f9KYVWlUgRY6oc&#10;hjnnCmz3s7GT3sROfxv76tPYCaOj54G364YpVTrZZYpIMbC3i3ULgbpE4d3E87wm+d/0ff/BRBYm&#10;UhSZipUxfS/FdjsLO+Ut7NRx2DHPYd8Zg+l0OqZ9T0yZsskuU0QOYXsL7veBuUDN2J/8dnnoiEhx&#10;YspXwPS5ENulD/bdsdh3/4d98yXspDcwHXpjOvXGlC2/7w2JiOynvY0qv6QQ6xBJSaZsOcxp52I7&#10;n46dNiHqRh/3KnbyW5gOPTCdz8CUr5jsMkXkEJLw+1o8z2sF3Ov7fnvP844Fnoy99SnQ3/f9MNE1&#10;iCSaKV0G0/1sbIde2OnvYCe9gX37Ney746Lr3136YCpVSXaZInIISOiUUJ7n/QN4GigZW3QXMMT3&#10;/ZOJJnbpncj9ixQ2U7IUTpczcO5+CnPulVC2PHbyW4Q3XEH4yhPY1T8lu0QRSXGJbnF/RnTv94ux&#10;12f6vm89zytBdN38twTvXyQpTImSmA69sCd3xc6Zin17DDZnAnbGJEybDtFkLtV2HjoiIrJv8dzH&#10;vdDzvP6e55XZ3437vv8GsDXfaxubA30ZUJXo/nCRQ5bJyMA5pSvOHcMxlw6Gw2pgZ06KJnJ59j/Y&#10;779JdokikmKMtXsfIO55XhvgT0AX4DVguO/7y+Pdged5dYGRvu+32Wn55cDJcQyC0wh2OWTYbdvY&#10;MHMya0c9y9avvgDHocxJnSjf7zJK1GuQ7PJEpGjZ7SMK99lV7vv+bGC253mVgPOA/3metwoY5vv+&#10;6P2pwPO8t4Brfd//DFgHbIvnc6tWrdqf3aS8zMzMYnfMOzukz0FWE+w/H8RZNJdw/Cg2zJjEhhmT&#10;oHlrnJ4eps5RwCF+DuJQ3I8fdA6g+J6DzMzMPb4X1zXuWGhfCFxOdF3aBy7yPK+37/sX7Uct9wLP&#10;e573B7AB6L8fnxU5ZBjHgePb4DRvDUsWEI4fBQvnEC6cA01a4PTqB3v5jysixdc+g9vzvJeBHsA4&#10;4M++78+JLR8O/Livz/u+vxJoE/t6DnDSwRQscigxxkDTFjhNToCPFhOOGwVL5hMumc9PzU/EdjoD&#10;c/SxyS5TRIqQeFrcy4G/+b6/w30svu9v9TyvbWLKEilejDHQqBnOscdB7jLCcaPYtHAuLJwLWdlR&#10;C/yYJtF6IlKs7XNwGoDneT2ArkTXpMf6vp+T6MLyscXt+kZxvaaTn84BVF3zEz++8Dgs+yBacNQx&#10;OD37QXbzYhHg+h7QOYDiew5i17h3+x89ntvBbgEeILq2vQF40vO8QQVZoIjsquSxTUkbfAvOPx+A&#10;41rB558QDruN8K5rsYvnYkNNOihSHMXTVX4hcLzv+78BeJ73ADAbGJbIwkQkYuodTdrAf2K/XoEd&#10;72MXziZ87G6oVQ/Tw8Mc3xrjpCW7TBEpJPEE9y9Et27lWQOsT0w5IrInpnZ9zIDrsau+wk4YjZ03&#10;E/vUfdiatTA9+2JanIJJU4CLHOriCe4FwFue5z1JNAvaBcBXnuedCeD7/usJrE9EdmIy62D6X4vt&#10;fW40lercHOwzD2HHvhpNpXpie0x6wp8fJCJJEs//7rx7Ua7daflfiWY1U3CLJIGpkYm5ZBC2Vz/s&#10;O69hZ03BvvAIdtwoTLezMG07YTIykl2miBSweGZOaw/geV46YHzf35LwqkQkbuawGpgLrsL28KLH&#10;ic6YiH15OHb8KEzXMzEnd8WULLnvDYlISohnVHl1z/PeBn4HNnmeN9XzPE3pJFLEmCqH4ZxzBc49&#10;T2O69IGNG7CjRhDe0J9w4uvYTRuTXaKIFIB4nsf9KDAXqAFUB2YCwxNZlIgcOFOxMk7fS3HuGYHp&#10;0Re2bMaOeT4K8PE+dsPvyS5RRA5CPNe4s3zf9/K9vsXzvLifDiYiyWHKV8D0uRDbpQ926jjslP9h&#10;33wJO/ENTMfemE69MWXLJ7tMEdlP8bS4MzzPK5X3IvZcbj1qUyRFmLLlcHqfg3PvCMyZF0FaGnbc&#10;q4TX9yd8/QXs2jXJLlFE9kM8Le5XgSme5z0Xe30pMCZxJYlIIpjSZTDdz8Z26IWd/k40kO3t17Dv&#10;jsWc0h3TtQ+mUpVklyki+7DPFrfv+3cAzwBdgG7A88BtiS1LRBLFlCyF0+WMaBDbeX+CchWwU94i&#10;vOEKwleewK7+ad8bEZGk2WuL2/O8DKCk7/vPAc95ntcY+MT3fXWVi6Q4k1EC074n9uQu2NlTo8lc&#10;ciZgZ0zCtOkQTeZSrWayyxSRneyxxe15Xi2iR3r2yrf4JmCpbgcTOXSY9AycU7ri3DEcc+lgOKwG&#10;duYkwpsGED77EPb7b5Jdoojks7eu8vuBZ33ffzVvge/7/YCXgPsSXZiIFC6Tno7TpiPO7Y9i+l8L&#10;NWth5+QQ/msg4VP3Y79dmewSRYS9d5Vn+75/7m6W3w0sS1A9IpJkxknDtGqHbXEyLJ5LOG4Udv5M&#10;7PyZ0Lw1Tk8PU+eoZJcpUmztLbg3726h7/uh53mbElSPiBQRxnGgeRucZq1hyQLC8aNg4RzChXOg&#10;SYsowI90k12mSLGzt+Be63lefd/3V+Rf6HneUURPCRORYsAYA01b4DQ5AT5aTDhuFCyZT7hkPhx7&#10;HE7PfpisRskuU6TY2FtwPwCM9TxvEDCb6Hr4icDDRN3lIlKMGGOgUTPSGjXDBssIx70aBflHiyEr&#10;G6dXPzimSbSeiCTMHoPb9/1xnudVAEYAdWOLc4Hbfd8fWRjFiUjRZNxs0tw7sZ99TDjeh2UfED64&#10;DI46BqenB9nHK8BFEmSv93H7vv8K8IrneVWA0Pd9zY0oItuZBg1JG3wL9stPowBf/D7hsNuhboMo&#10;wJu2jK6Vi0iBiWfKU3zfX53oQkQkdZl6R5M28J/Yb1Zgx/nYhbMJH78bjqiL6dkPc3xrjJOW7DJF&#10;DglxBbeISDxMrfqYAddjv/saO2E09v0Z2Kfuw9ashenZF9PiFEyaAlzkYKgPS0QKnDm8Ns7l1+Dc&#10;+TimbSf46TvsMw8R3vxnwvcmY7duSXaJIilrny1uz/Pq7LTIAht83/8lMSWJyKHCVM/EXDII26sf&#10;9p3XsLOmYF94BDv2VUz3szBtO2MyMpJdpkhKiafFPQtYASwBFgNfAqs8z/vW87w2CaxNRA4R5rAa&#10;OBdchXPXU5iOvWHdb9iXnyC88QrCKf/D/vFHsksUSRnxBPcU4FLf9yv5vl8F8Ige7dkLeCiBtYnI&#10;IcZUOQznnCuiR4p27QMbN2BHjSC8oT/hxNexmzYmu0SRIi+e4G7q+/5/8174vv8acLzv+4uAEgmr&#10;TEQOWaZiZZyzL8W5ZwSmhwdbt2DHPE84pH80N/qG35NdokiRFU9wp3uel533IvZ1mud5pQBdnBKR&#10;A2bKV8DpcwHOvSMwp50H1mLfeplwSH9+e/EJ7O/rkl2iSJETz+1gQ4BpnuctJwr6o4HzgNuANxJY&#10;m4gUE6ZMOUzvc7CdTsNOexs7+U3WvjoC3ngZ074HpvPpmAqVkl2mSJGwzxa37/sTgCyi69n3Ag19&#10;358K3On7/s0Jrk9EihFTugxO97Nw7nmaSv2vhlKlsO+8Fl0DH/UMdo3mghKJ53YwB+gP9IitP8nz&#10;vLt931cflogkhClZivJ9zmdt87bY9yZHt5JNeQs7bQLmpM6YbmdhqlZLdpkiSRFPV/k9QFPgP0Qt&#10;9CuB+4GrE1iXiAgmowSmfU/syV2ws6di3x6DnTYBO3MSpk0HTPezMdVqJrtMkUIVT3B3A07wfX8L&#10;gOd544EPUXCLSCEx6RmYU7pi23TEzpuOnTAGO3MSdtYUTKt2mB59MTVrJbtMkUIRz6hyJy+0AXzf&#10;/wPQfIUiUuhMejpOm444tz+KueLvULMWdk4O4b8GEj51P/bblckuUSTh4mlxL/Y87yHg0djrgUSz&#10;qImIJIVx0jAtT8GecBIsnks43sfOn4mdPxOanYjTqx+mzlHJLlMkIeIJ7oHAMGA2YICJwF8TWZSI&#10;SDyM40DzNjjNWsOSBYTjR8GiuYSL5kLjE6IAP9JNdpkiBWqfwe37/lrgkvzLPM9rBOi+DBEpEowx&#10;0LQFTpMT4KPFhONGwdIFhEsXwLHH4fTsh8lqlOwyRQrEgT6Pew5QoSALERE5WMYYaNSMtEbNsMGy&#10;qAX+0WLCjxZDViOcnv2gYdNoPZEUdaDBre96ESnSjJtNmpuN/fyTqAW+7APC3H/BkS5Or36QfbwC&#10;XFLSgQa3LdAqREQSxBx1DGmDb8F++Snh+NHRYLZht0PdBjg9PWjaMrpWLpIiDjS4RURSiql3NGkD&#10;b8R+swI7fjT2g1mEj98NR9TF9OyHOb41xklLdpki+7TH4PY8bx27b1kboEzCKhIRSSBTqz7mT9dh&#10;v/saO2E09v0Z2Kfuw9asFU3k0vIUTJoCXIquvbW4s/fynohISjOH18Zcfg229znRTGxzc7DPPoQd&#10;OzKaSrV1e0y6nlwsRc8eg9v3fU1BJCKHPFM9E3PJIGyvftHDTGZNwf73Uey4UZjuZ2HadsJklEh2&#10;mSLbaUSGiAhgDquBc8FVOHc/jenYG9b9hn35CcIbrySc8hb2jz+SXaIIUAiD0zzPawXc6/t+e8/z&#10;jiOahW0r8Adwke/7PyW6BhGReJnKVTHnXIHtcTZ20pvYaW9jRz2DnTAG0+UMzKndMaU0zEeSJ6Et&#10;bs/z/gE8DZSMLfoPMND3/Q7AG8CQRO5fRORAmQqVcc6+FOeeEZgeHmzdgn3tBcIhVxCOG4Xd8Huy&#10;S5RiKtFd5Z8BffK97uf7/tLY1+nAxgTvX0TkoJjyFXD6XIBz7wjMaeeBtdi3XiYc0p/wrZexv69L&#10;dolSzCQ0uH3ff4OoWzzv9Q8Anue1IXp4yUOJ3L+ISEExZcrh9D4nCvAzL4b0dOy4UYTX9yd87QXs&#10;2jXJLlGKCWNtYidB8zyvLjDS9/02sdf9gBuA0+Mcua5Z2kSkyAk3beT3t19n7esvEq7+GVOyJGW7&#10;nUmFsy4irWq1ZJcnh4bdzslbqDOneZ53AXAlcKrv+3H/erpq1arEFVUEZWZmFrtj3pnOgc5BShx/&#10;q/bQvC3mvcnYd15j/VsjWT9+DOakzphuZ2EOMsBT4hwkWHE9B5mZmXt8r9CC2/M8B3gYWAm84Xme&#10;Bab7vn9bYdUgIlLQTEYJTPue2JO7YOfkYN8eg502ATtzEqZNhyjAqx+e7DLlEJLw4I51h7eJvaya&#10;6P2JiCSDSc/AnNwF26Yj9v3p0XSqMydhZ03BtGyH6dkXU7NWssuUQ4AeMiIiUoBMWhqmTQfsie2w&#10;C2Zhx/vRdKrvT8OccBKmp4c5om6yy5QUpuAWEUkA46RhWp6CPeGk6FGi433s/JnY+TOh2Yk4Pfth&#10;6h6V7DIlBSm4RUQSyDgONG+D06w1LF1AOG4ULJpLuGguND4Bp6eHOeqYZJcpKUTBLSJSCIwx0KQF&#10;TuMT4OPFUYAvXUC4dAE0bIrTqx8mSw9llH1TcIuIFCJjDBzbjLRjm2GDZYTjR8HHHxJ+/CFkNcLp&#10;2Q8aNo3WE9kNBbeISJIYN5s0Nxv7+SeE4/2oBZ77LzjSxenVD3t472SXKEWQHuspIpJk5qhjSBv0&#10;L5ybHoTjToQvAsJht/PD3y7CLpqLDcNklyhFiFrcIiJFhKnbgLSBN2K/WYEdP5otH8yCx++GI+pG&#10;t5Ed3wbjpCW7TEkyBbeISBFjatXH/Ok6qm39gx9eeAz7/gzsU/dja9bC9OiLaXkKJk0BXlypq1xE&#10;pIjKqFMf5/JrcO58HHNSZ/jpO+yzDxHe/GfCmZOwW7cku0RJAgW3iEgRZ6pn4lz8V5y7nsSc2h1+&#10;/Rn730cJ/zmAMGcCdsvmZJcohUjBLSKSIkzV6jjn/xnn7qcxHXvDut+wrzxBeOOVhFPewv7xR7JL&#10;lEKg4BYRSTGmclWcc67AufdpTNc+sHEDdtQzhDf0J3znNeymDckuURJIwS0ikqJMhco4Z1+Kc88I&#10;TA8Ptm7BvvYC4ZArCMeNwm74PdklSgIouEVEUpwpXwGnzwU4947AnH4eWIt962XCIf0J33wJu35t&#10;skuUAqTgFhE5RJgy5XB6nYMzdATmzIshPR073o9a4GOex65dk+wSpQAouEVEDjGmVBmc7mfh3PM0&#10;xrscSpXGTnw9ugY+agR2zS/JLlEOgiZgERE5RJmSpTCdT8ee2h373hTsO2OwU/6HnTYBc1JnTLez&#10;MFWrJ7tM2U8KbhGRQ4jjOIQ7zW1uMkpg2vfAntwZOycH+/YY7LS3sTMnYVp3wHQ/G1P98CRVvCtj&#10;DNbaZJdRZCm4RURS3MaNIUuXriEn51tyc9eQlVWJ9u2PoHHjSpQu/f9XRE16BubkLtg2HbHvT8dO&#10;GI19bzJ29ruYlu2i6VQPr5WUY9iyxZKbu46pU79l2bLVZGdXoUOHI6hUqWpS6inKTAr8VmNXrVqV&#10;7BoKVWZmJsXtmHemc6BzUNyPH+I7Bxs3hrz22pcMGTKX/D/OjYF77z2Rs86qt0N452fDbdgFs7Dj&#10;fVj1FRiDOeGkKMBr1SvAI9m7LVssY8d+zaBB7+1yDI891o4ePTLJyChezyfPzMwE2O1Ba3CaiEgK&#10;W7p0zS6hDWAtDBkyl6VL9zyS3DhpOC1PwbllGM6fb4Da9bHzZxLeNohtj92NXfl5gquP5Oau2yW0&#10;ITqGgQOnk5u7rlDqSBXqKhcRSWE5Od/uEnh5rIWcnFW0bFllr9swjgPNW+M0OxGWLiAcNwoWzyVc&#10;PBcan4DT08McdUwCqo9MnbqvY/iWRo0qJGz/qUbBLSKSohzHITd37/dm5+au2e2Atd0xxkCTFjiN&#10;T4CPF0cBvnQB4dIF0LApTq9+mKzsgip/+z6XLVu913WWLftVA9byUXCLiKSoMAzJyqrEO+98vcd1&#10;srIqxRXa+Rlj4NhmpB3bDBssIxw/Cj7+kPDjDyGrEU7PftCwabTeQbLWkp1dhXHjVu5xnezsygrt&#10;fHSNW0QkhbVvfwR7yk9joH37zIPavnGzSbvmDpwh90HjEyB3OeFD/yK89zrskvkFEqgdOuzrGI44&#10;6H0cShTcIiIprHHjStx774m7BJ8xMHRoaxo3rlQg+zFHHUPaoH/h3PQgHHcifBEQPnIH4Z3XYBfO&#10;we5nqz6/rKzyDBt20m6P4fHHTyUrq/xBVn9o0e1gRZBug9E5AJ2D4n78EP85yLuPe9q0VQRB3n3c&#10;mbvcx12Q7DcrsONHYz+YFY0gO6IupqeHOb4Nxknb7+3l3cedk/Mty5b9SnZ2Zdq3P4K2beuzphhO&#10;0bq328F0jVtEJMWVLu3QsmUVWrasEvdAtINlatXH/Ok67HffRBO5zJuOfep+bM0jMN37Ylq1+7/2&#10;7jzcquq84/h37csURFJDHpQrERIQGRUElUGQQawMFhR9cQxpFI1DTDWxFY1SH2v0aa3aBoMGB7SK&#10;8koCVBBlENGrYgIRAinWYKLRaOJQolIUwbP6xz70uV4vcEHO2Xff+/s8j4/nnmGvdy/P8XfW3vus&#10;Raioe4A3bRro0aM1PXq0/syFaC1bNucvWhvlM3SoXESkASlHaFcX2rUnOfcykuunE44dCe/8iXjv&#10;bRSuuZDCM4uJ27ft8TZzcCQ4UwpuERH5wkLbdiSTvktyw52EoaNg07vE+6dRuPo7FJY/Rtz2SdYl&#10;NhgKbhER2WdCm7YkZ11I8qMZhBEnwYfvE2fdQWHK+RSWzidu3Zp1ibmn4BYRkX0uHNCG5PTJJDfN&#10;IPz1KfDxFuLsu9M1wR//GfHjLVmXmFsKbhERKZnQ+gCSU79FctNdhDEG27cRf3YfhSsnU1jwMHHL&#10;5qxLzB0Ft4iIlFxo1Zpk/NlpgI87E4A4fxaFK8+jMO8B4uYPMq4wPxTcIiJSNqFlK5Kxp6eH0E+Z&#10;BE2aEhd6OgKfM5P4waasS6z3FNwiIlJ2oUVLklETSG6cQbBzocWXiE/8nMKUyRQenkHc1PgmXakr&#10;TTY61ygAAA44SURBVMAiIiKZCc1bEEaOIw4dRaxaSnx8DnHZo8QViwjHjmT7pIuyLrHeUXCLiEjm&#10;QtNmhGGjiYNHEp9fTlw0h/jUIt56ZjFhwHDCqFMJbdtlXWa9oOAWEZF6IzRpShh8AnHgCOILK6hY&#10;MpftVUuIzy0jHH0cYfRphHbtsy4zUwpuERGpd0JFBWHgcA46+Qz+uGAOcaETVy4nvvAUoe+gdEGT&#10;9h2zLjMTCm4REam3QkUFyVGDiX0HwZoXKCycTVxVRVxVBb37k4w1QofOWZdZVgpuERGp90KSwJED&#10;SPr0h3WrKCyYDWtWUlizEnr1IxljhE5dsy6zLBTcIiKSGyEEOPwokl79YMOaNMDXraKwbhV0O4Jk&#10;zETCYT2zLrOkFNwiIpI7IQTo3oeK7n2IL69PA3zDWgob1sKh3UnGToRuvdPnNTAKbhERybXQpScV&#10;l/ckvvIShYWejsBvnQpf75IGeK9+DSrAFdwiItIghE5dqbj0WuJrG9MAf3ElhR9fD4d0Ihlj0PuY&#10;9Fx5zim4RUSkQQkdOlNx0VXEN15Nf0a2+lkK02+EgzukvwPvN4iQVGRd5l4r+VcPMzvGzJbXuO8W&#10;Mzu/1G2LiEjjFdp3JLng70muu53Qfxi89Tpxxs0Upl5C4bkniZ9+mnWJe6WkI24zuwI4B9hc/Pur&#10;wP3AocBLpWxbREQEILRrTzj3MuJJp6dTqT7/JPHe24gLHk6nUh0wjNCkadZl1lmpR9wbgZOr/d0K&#10;mAr8R4nbFRER+YzQth3JpO+S3HAnYego2PQu8f5pFK6+gMLyx4jbPsm6xDopaXC7+1xge7W/X3X3&#10;XwIN5/I+ERHJldCmLclZF6ZLih7/N7D5A+KsOyhMOZ/CkvnErVuzLnGXcnFxWmVlZdYllF1j3Oea&#10;1Afqg8a+/6A+gBL2QWUldO/Fp9+6mA/nPsjmhY8Q/W7CEz+n1cln0WrMaSQt9ytN219AuYL7C42w&#10;33zzzX1VRy5UVlY2un2uSX2gPmjs+w/qAyhjH5x4KuHYE2Dpf1J4cgHvz5zG+4/cRzj+JMLwsYSW&#10;rUpfQzW7+rJSrh+0xd38LSIikqnQqjXJ+LNJbrqLMO5MAOL8WRSuPI/C3AeImz/IuMJUiLHeZ2hs&#10;bN849S1bfQDqg8a+/6A+gGz7IH68hfjUIuLiefDh+9C8BWHoKMIJ4wmtDyhp28URd61Hq/M/hYyI&#10;iEgJhBYtSU6cQHLjXYSJ50KLlsQn5lKYMpnCwzOIm97LpK5cXJwmIiKSldC8OeH4ccTjRhGrlhIf&#10;n0Nc9ihxxSLCsSMJJ04gtGlbtnoU3CIiInUQmjYjDBtNHDyS+PzydDKXpxYRn1lMGDCcMGoCoW3p&#10;fwWg4BYREdkDoUlTwuATiANHEH/xNPExJ1YtIT67jHDMEMJoI7RrX7L2FdwiIiJ7IVRUEAYMIx4z&#10;hLj6uXRBk5VPEV9YQeg7iDDGCO077vN2FdwiIiJfQEgqCEcNJvYdBGteoLBwNnFVFXFVFfTuTzLW&#10;CB0677P2FNwiIiL7QEgSOHIASZ/+sG4VhQWzYc1KCmtWQs++JGMnEjp1/cLtKLhFRET2oRACHH4U&#10;Sa9+sGEthYWzYf1qCutXQ7cjSMZMJBzWc6+3r+AWEREpgRACdO9NRffexJfXpyPwDWspbFgLh3Yn&#10;GTsRuvVOn7cHFNwiIiIlFrr0pOLynsRXXqKw0NND6bdOha93IRkzEQ7vV+cAV3CLiIiUSejUlYpL&#10;ryW+tjEN8BdXUph2PRzyDZIxBr37p+fKd0HBLSIiUmahQ2cqLrqK+MarxMceIa6qojD9Jji4A2H0&#10;aTD+9J2+VnOVi4iIZCS070hy/hUk191O6D8M3nqdOOPmXb5GI24REZGMhXbtCedeRjzpdOKKRbt8&#10;roJbRESknght2xFO+/Yun6ND5SIiIjmi4BYREckRBbeIiEiOKLhFRERyRMEtIiKSIwpuERGRHFFw&#10;i4iI5IiCW0REJEcU3CIiIjmi4BYREckRBbeIiEiOKLhFRERyRMEtIiKSIwpuERGRHFFwi4iI5IiC&#10;W0REJEcU3CIiIjmi4BYREckRBbeIiEiOKLhFRERyRMEtIiKSIwpuERGRHFFwi4iI5IiCW0REJEcU&#10;3CIiIjmi4BYREckRBbeIiEiOKLhFRERyRMEtIiKSIwpuERGRHFFwi4iI5IiCW0REJEealLoBMzsG&#10;uMndh5lZJ2AmUADWu/vFpW5fRESkISnpiNvMrgBmAM2Ld90CXOXuxwGJmY0rZfsiIiINTakPlW8E&#10;Tq72d193f6Z4exFwfInbFxERaVBKGtzuPhfYXu2uUO32h8CXS9m+iIhIQ1Pui9MK1W7vD/ylzO2L&#10;iIjkWskvTqvhV2Y2xN2fBkYBT9blRZWVlaWtqh5qjPtck/pAfdDY9x/UB6A+qKncwf0DYIaZNQU2&#10;AHPq8Jqw+6eIiIg0DiHGmHUNIiIiUkeagEVERCRHFNwiIiI5ouAWERHJEQW3iIhIjpT7qnKpxsya&#10;APcAHYFmwA3u/mjxsVuAl9z9p9lVWHq19QHwB+DHpJP3bAW+6e7vZFVjqe2kDzYCO/7b/xY4z90L&#10;tW6gAdjNZ+FM4BJ3H5hdhaW3k/fB68AC4OXi06a7+yOZFFgGO+mDlaRTZ/8VUEH6/4PfZ1VjfaAR&#10;d7bOBt519yGkv2ufZmZtzOwx4KRsSyub6n1wIjANuA242N2HA3OBKzOsrxxq64MbgCvdfTDpTyIb&#10;+vvhc58FADPrA3w7y8LKqLY+OBL4V3cfXvynwYZ2UW198M/AA+4+FLgG6JpdefWDRtzZcmDHBzEB&#10;tgGtgKmkb9rGoHofVJD2wUR3f7t4XxPgoywKK6PP9YG7nwJgZs2Ag4D3M6qtXD73WTCzrwD/BHyP&#10;dMTV0NX2/4O+QFczG0965OV77v6/GdVXDjX7YDswEPi1mS0Bfk/6fmjUFNwZcvctAGa2P+mb9Wp3&#10;fw14zcxGZ1pcmeykD94u3jcQuBgYkl2FpVdbHxT/PgRYSjo18NrMCiyDWvrgGuBu4HLS0yUNfiKm&#10;Wvrgh6QrK97l7i+a2VXAPwJXZFZkie3ks3A/8J67jzSza0iPwE3Nrsrs6VB5xszsa6RTv97n7rOz&#10;ricLtfWBmU0EfgKMdvf3sqyvHGrrA3f/g7t3Ae4Ebs2yvnKo3gek5/g7A9OBh4Buxes+GrQa74OH&#10;gXnu/mLx4blA78yKK5Na+uBd4NHiw4+SHoVo1DTizpCZHQg8QXo+d3nW9WShtj4ws7OB84Gh7t7g&#10;F6LZSR/MB77v7htJV9L7NMMSS24nn4Vexcc6AA+5++VZ1VcOO+mDJ8zsEndfBYwAVmdWYBnspA+q&#10;gNHAg6RH336TUXn1hoI7W1NIr5S8xsyuBSIwyt23Fm83BjX7oALoAbwGzDWzCKxw9+syrLHUansf&#10;XA3MNLOtwBbgvAzrK4ddfRYai9r64DLgNjP7BPgT6Rfahqy2PpgE3G1mF5Je63FmhvXVC5qrXERE&#10;JEd0jltERCRHFNwiIiI5ouAWERHJEQW3iIhIjii4RUREckTBLSIikiP6HbdImZlZAvwdcAbp79ab&#10;ka4Ada27f7IX27sXWOfudZpZzMxGADeT/ka2XbGGN4oP30g62UWdt7eHtR4HTHP3Xnv4ugLwVXf/&#10;nxr3fx/o6e5/uw/LFKnXFNwi5XcH8GVguLt/aGZfAmaRLqQxqdSNu/syoA+AmU0F2rj7pTseL8M8&#10;+XszecSuXqPJKKRRUXCLlJGZdSQdaR+0Y5Und//IzC4ABhZD/I/A0cXpTjGzxaTrkz9Z/Pcg0pWj&#10;5rn7D2tsvxvpsqhfIR1J/7u7z9yLUgeZ2QTgQGA9cEaxzo+B+cDhwFmks7r9W832zGw/4F7S+cYL&#10;wGp3v6C47f3N7CHS5RmbA5Pd/Vkzaw3cTjofdwF4HJhSXIc8FPevSbEPjgf+DLxNugiLSKOhc9wi&#10;5XUk8JuaSzO6+9vuPs/dPwJmApMBzKwT0IX0UPr1QHN3P4x0xDzIzP5/5TQzqyBdUekf3P0oYChw&#10;hZkdvRd1VgLDi223B04p3t8MmO/u3UhXLJuzk/ZOBlq5+5HA0cX6vlHcxsGka0z3AX5KuuIVpIH8&#10;bvEwej/gCOAHNeq6mPTLQFfgBOCQvdg3kVxTcIuUV4Hdf+6mA+cUg3gyMMPdI+kiE3cDuPs2dx/m&#10;7k9Xe10XoBNwj5m9CKwAWlA8LL6H5rn71uJodz3QttpjVXVorwroYWbLSZdhvM3df1d83SvFRTMA&#10;1lTb9onAtB37R3pKYce69DsOh48AZrn7p8UlIB/ci30TyTUdKhcpr1+QLlG5X/VRt5kdTLp85wR3&#10;/62Z/RoYT3o4ul/xadupdj7XzNqTHqreoQLYVBzl7nhOW/buUPK2arcjn10Pe/Pu2nP3T8ysM+ko&#10;fDiwzMwuAd7bxbZrfqFJgKY17qtZy/a67pBIQ6ERt0gZufubpKPEe8xsf4Bq53bfqbYa1k+AfwFW&#10;uvufi/ctBSaZWTCz5qSHqYdU2/x/Ax+b2VnF7X6NdLRcqvWLd9qemX0HmOnuS9x9CulSjT2Lrwu1&#10;bq24nGNxW81JV8JaXOM1jwPfNLPmZtYCmLiP90mk3lNwi5TfRcAG4Dkz+xXwPGngTa72nAVAK9LD&#10;5jtcRzpaXUu6LvMCd5+348Hi4eVxwHlmtpY05K529+f3sL6aV2nH2m7vpr37gcTM/svMfgnsT3oR&#10;W23b3+FS4EAzW1fcx5eAH9V4zZ2k+74eWA78ruZGRBo6LespUg+Z2UDgzj39vbOINHw6xy1Sz5jZ&#10;TOA44JyMSxGRekgjbhERkRzROW4REZEcUXCLiIjkiIJbREQkRxTcIiIiOaLgFhERyREFt4iISI78&#10;H30JlNx5+4x7AAAAAElFTkSuQmCC&#10;">
 +
</div>
 +
<div class="clear"></div>
 +
 +
Please refer to the <a href="https://github.com/genspace/iGEM-qPCR-Copy-Number-Analysis/blob/master/qpcr_pSB1C3_Absolute_Quantification.ipynb">Jupyter Notebook</a> for qPCR copy number analysis.
  
 
</p><p class="c0"><span><b>pSB1C3 absolute quantification run #4</b></span></p><p class="c0"><span>Lysate from 100,000 stationary phase cells harboring K909006-pSB1C3 was compared against a 2-point standard of 10</span><span class="c1">5</span><span> and</span><span> 10</span><span class="c1">6</span><span> 1.1x10</span><span class="c1">6</span><span> copies.  The 1.1x10</span><span class="c1">6</span><span>-copy standard was created using lysate from 10</span><span class="c1">5</span><span> cells as well as 10</span><span class="c1">6</span><span> copies of purified plasmid.  This point was created to test for variance in amplification efficiency of plasmid vs. genomic template.</span></p><p class="c0 c2"><span></span></p>
 
<div class="img-block">
 
<!-- fig4 -->
 
<img src="https://static.igem.org/mediawiki/2016/f/f4/T--genspace--pSB1C3_Absolute_Quantification_4.png" alt="">
 
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAe4AAAGMCAYAAAAcK0EHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz&#10;AAALEgAACxIB0t1+/AAAIABJREFUeJzs3Xd4FVX+x/H3mST0jhQjVTEjEkBQQEBFeldRGewVXVZ2&#10;YdVdRVfXXtBVVyxYsK0FGbAtRSkSihQBASnqxIJYsCMCAlLm/P6YG36hXyA3N5d8Xs/DQ+7cuTPf&#10;GUI+OWfOnDHWWkRERCQ1OMkuQEREROKn4BYREUkhCm4REZEUouAWERFJIQpuERGRFKLgFhERSSEK&#10;bhERkRSSnuwCRAqT67qnANOAJ4IguCrf8ouBfwdBUC0B+2wH5ADlgiDYEMf6jYGqQRBMO4h9VgCu&#10;B84GagPfA+OAu4Mg+P5At3sAdRwGdA6CYGTsdQ4wPwiC61zXNcBzQF/gR+BW4P4gCKoXwH53OIeu&#10;64ZAryAIJhzstvex3y7AO0C9IAi+SuS+pPhSi1uKm/OBXOAc13VL7vReImcj2p9tvwUce6A7ioXl&#10;+0A74CrABS6N/b3Add2jDnTbB+A+oE++132A22JftwYuii1rC7zKQRz3TnY+hzWByQW07d1yXbcc&#10;8DSJ/T4SUYtbig/XdUsQtUD/BjwJnAW8ktSids8c5Of/A6wB2gVBsC227GvXdWcQtQafAU49yH3E&#10;a4djCYJgTb6XlQEbBMGkfMv+SNB+fyyg7e7NA8AXQK1C2JcUY0ZTnkpx4brumcAooAbwIlAyCIJO&#10;sfcuBu4HHgKujX3kv8DfgyAIXddNIwrEs4GKwAfANUEQzI99/ijg30St3BB4Pfb++lhX+VSgPFAN&#10;WAFkB0HwUb59/zsIgmqxruR2RK226UEQdHBdtwbwCNANWA+MB64NgmDtbo6xMlG3eJ/ddQu7rnsi&#10;MBtoFATBx67rriDqnn489n7d/PW5rls9dk46x477a+CuIAiei62fA0wHjgO6AD8DtwZB8KzrurcA&#10;t8R2bYMgSMvrKgeWE3WTEzvW24CV5Ltc4bpuE6IwPBFYDQwPguDe2HstgHuAVkQNkA+BQUEQzNvD&#10;OdzeVe66bgZwI3AxcDiwIHY+5+3lmG4LguCZnc9nvvPameiXwXOBOairXBJIXeVSnJwPzAqCYDVR&#10;sJ4aC6o8hxH9oD41tu55wHWx9/4K9AZOI+qCzQVGA7iuWwl4j6i12Jao6/ckopbt7uzut+W8ZWcC&#10;3xAFy5mxZW8A24hCqhdwJFG38u4cTxRkc3b3ZhAEc4FNQJs9fH7n+l4kOi/tgYZEXdDDXdfNPxbg&#10;OmAC0Xl5A3g89v6/AR8YS9RVnd+rwIWxfdWMrbt9367rVgXeJToXJwBXAkNc170k1iU9AVgINCY6&#10;L+uJghN2fw7zexS4DPgzUTgvBybHfkHa0zE9ttMxbxer56lYjetRV7kkmIJbigXXdSsCPYDXYove&#10;JGoZX5Jvta3AeUEQLAuCYCJwJ9E1YoB6RIH3dRAEXwLXABfHBlhdQPR/6aIgCD4OgmBmbLt993A9&#10;eY9d4UEQ/EoU0uuCIFjjum57IBu4MLbthUSB18113Ya72cRhsb/X7WkfRK3Xw/byfv76xgJ/CoJg&#10;eRAEXwB3AyWArHzr5ARB8FTsvNwUe79pEAS/AxuBP4Ig+Gmn4/yDqDufIAh+2s2gvXOAzcAVQWQi&#10;UdCuB8oAQ4EhQRB8GQTBEmA40Xna5Rzm32js++Ay4G9BEEwMgiCIbfdr4C/7OqY9nK9/A+8GQTBl&#10;D++LFCgFtxQX/Yh++L4BEATBL0TdoRfnW+fbIAi+y/f6A+CI2Ajt4UA5omvFM4E/AR8FQWCJWqKL&#10;gyDYnO+z84mCp9FB1n0sUBb41XXdda7rrgMCol86jtnN+r/E/t7bddaKxEIzDsOBE13XHea67jvA&#10;R0QtyrR863ya90UQBHm/MGTEuf09aQgsCYJga75tjwyCYEzsevUIYKDruiNi1+5fIL6fZ1mx9ebm&#10;264ldvkg33pxHZPrup2IekGuiS062PEJIvukwWlSXJwf+3uF67p5ywxgXNftGHu9bafP5AXBliAI&#10;Atd16wNdge7AIOAvruu2ImqJ745hx4CD3Xej7u3/YTrwJdCJXUPhh92sv4Co56Bl7HM7cF33eKJf&#10;BObvoZ70fOsaYCKQSdS1PZWoWznY6TOb2dXBBtjmPW3Ddd3DgXnAJ8DbsdqqAS/Fsd1Ne9iuw47/&#10;VvEe03mxfX8b+75yYustd133rrxr8iIFSS1uOeS5rluH6JrzLUTdnXl/jifqer0stmqt2PXqPG2A&#10;lUEQbHRd9wKgXxAE44IgGEh0a1X12HY/Bo7b6faylkQh+PFO5eQFQvl8y3buTs8fph8TBef6IAi+&#10;iHVXbyMaKLfL/c6xbmIfuCU2CAvXddu6rrvEdd1ewB3AB7Eu97x6dq4lb//NgA5A9yAIbg+C4E2i&#10;keAQfzAf6PXeXCA7NiiQ2HH8y3XdUUQDwLYEQdA5CIIHY13UtePc72fAFna9xt+aqDdhf11H1DuQ&#10;9z11Vmzf3YEnDmB7IvukFrcUBxcQXWsdtvNIbNd1XwD6E7VA04GRruteTxRgNxBNYgJQAbjddd1f&#10;iH7A9yIKr4XAKuBfwH9d170dqAo8DkwOguCT2KCnvKD7geh66rWu6w4h+mF/yU71rgcaxgZDTY7t&#10;b5Trun8n6iJ/lKjb/ss9HO/fiC4D5LiuexvwOTAL+B9RqOQPrfnARbFu8FJEwZ4Xet8Tu+7vuu7L&#10;RL+sPBx7f+d74PdkPdDIdd26QRCsjPMzAC8TTcjyuOu6DwANYsc1mOiXjRqu6/YElhENnPsnRLf8&#10;xS5ZbD+H+a+vx34JewR40HXd34lG0A8G6hLdg71fgiD4mWjUObH9lyb6t/5q5+vrIgVFLW4pDs4D&#10;Xt3d7VNEIViCaET4R0RBNoPo2u6/gyB4GiB2u9SjseWfEI0gPjsIgs+DINhINBq9IlEX7mii2dnO&#10;yrcfG9uOJQrqhkTdzoOJfkHI72GiXzbeia1/GtG166mxP6uAHrH3dhG7ft86VsOjROHWi+j2tteB&#10;V2Otb4gC71uiUejPE/VKhLHtrIod5xVELf//AI8BS4h6K/Ykf13PE91ytTx2a1lcYteVuxNdx18c&#10;2+9tQRC8SNSj8DTR7WQfxurrH9tvXl3bz+FuarqB6LbA54jGMTQETo31Zuy87u6OaV80qlwSKuH3&#10;cXue1wq41/f99p7nVSP6D1eJ6HrSRb7vr0hoASKyg9i0nFuCIMhJdi0isv8S2uL2PO8fREGd1612&#10;H/CS7/unAjez+1GxIpJAQRBMUmiLpK5Ed5V/xo7zFLcFanmeN5mo+3JagvcvIiJySElocPu+/wbR&#10;4JY89YDVvu93JhqgMySR+xcRETnUFPao8l+IZmIi9vedcXxGAz1ERKQ42u1tl4Ud3DOJpp18GTiF&#10;aFTtPq1atSqRNRU5mZmZxe6Yd6ZzoHNQ3I8fdA6g+J6DzMzMPb5X2MH9d2CE53l/Bn4jus4tIiIi&#10;cUp4cPu+v5LYhA++739FdL+riIiIHABNwCIiIpJCFNwiIiIpRMEtIiKSQhTcIiIiKUTBLSIikkL0&#10;WE8REUkJixcv5vbbb6devXoA/P7772RmZnLTTTeRlrb90e1Yaxk+fDgrVqxg8+bNlC5dmsGDB3P4&#10;4Yfvcx+bN2/mrrvuYs2aNZQpU4YhQ4ZQsWLFHdYZOXIkU6dOpWzZsvTr14/WrVszcuRI5s2bhzGG&#10;devW8euvvzJmzBgAtm3bxh133EHPnj1p0aLFQZ8HtbhFRCRlNGvWjAcffJAHH3yQJ598krS0NGbN&#10;mrXDOvPmzeOXX37h/vvv5+GHH6Z37948/vjjcW3/rbfe4sgjj+Thhx+mc+fOvPjiizu8v2LFCqZO&#10;ncrw4cO57777eO6559i8eTPnnnsuDz30EA8++CDVqlXjhhuip/WuWrWKv/3tbwRBUDAnALW4RUQk&#10;RW3ZsoXVq1dTvnz5HZZXqlSJ3NxccnJyaN68OW3btuXEE08EYPr06bz00ktUqlSJsmXL0rp1a7p2&#10;7br9s0uXLuXcc88FoFWrVrsE98qVKznuuONIT4/is1atWnz++ec0bNgQgBkzZlC+fHmOPz56NPym&#10;TZv4xz/+wciRIwvsuBXcIiKy38LRz2E/mLXvFfeDOb4tTt9L97rOokWLuOaaa1i9ejWO49C7d2+a&#10;NWu2wzqu63LttdcyduxYHnnkEapXr85VV11Fo0aNGD58OCNGjKBs2bIMGbLrc642bNhA2bJlAShT&#10;pgwbNmzY4f0jjzySV155hY0bN7J582aWL19O7969t78/cuRIbr755h3WL2gKbhERSRnNmjXj5ptv&#10;Zu3atfzjH/+gZs2au6zzxRdfULt27e0BumDBAm699VaeeeYZKlSoQLly5QBo2rTpLp8tU6YMGzdu&#10;BKIQz1s3T506dTjjjDO4/vrrqV69Og0bNtx+DXzlypWUK1dur/OMFwQFt4iI7Den76Wwj9ZxIlWo&#10;UIEbb7yRq6++mhEjRlClSpXt733wwQesXLmSa6+9FmMMdevWpXTp0lSuXJlNmzaxZs0aKlWqRBAE&#10;tGnTZoftZmdnM3fuXFzX5f3336dx48Y7vP/bb7+xYcMGhg0bxu+//851111H/fr1t++3VatWCT92&#10;BbeIiKSkunXrctZZZ/HII49wyy23bF9+5pln8sQTT9C/f3/KlSuHMYZ//vOfAFx99dXceOONlC1b&#10;lj/++GOXbZ5++uncc889DBo0iIyMDG666SYARo8eTa1atWjdujVfffUVf/7zn8nIyGDAgAEYEz19&#10;85tvvtl+bTuRjLVF/nHXtrg90q24PsYuP50DnYPifvygcwCJPQdPP/00derU2WFwWlER627f7fO4&#10;dTuYiIhIClFXuYiIFEtXXHFFsks4IGpxi4iIpBAFt4iISApRcIuIiKQQBbeIiCSEtbBhwza2bi3y&#10;dy+lFAW3iIgUqG3bLMuXr+Wuuz7ktNMmcd55OUycuIqff95c4Pt64403DnobAwcO5Icfftjvz331&#10;1VdcffXVB73//aVR5SIiUqBmzPiRiy+eyrZt/9/SnjXrezp3rsV997WievWSBbavl156iT59+hTY&#10;9vZX3uQrhUnBLSIiBeabbzYyYMCMHUI7z+TJ3zB7dn3OOKP2AW77G4YOHUp6ejphGNK8eXPWrVvH&#10;ww8/zBVXXMH999/P77//zi+//MLpp5/OaaedxtVXX02DBg1YsWIFGzZs4NZbb6V69eqMGDGCBQsW&#10;UK1aNdauXQvATz/9xH/+8x82b97M6tWrueyyy2jbti2XXXYZtWrVIiMjg4EDB3LnnXcCULly5e21&#10;jRgxgsWLFxOGIaeccgrnnHPOAR1jPBTcIiJSYHJzf2P9+i17fP+RR5bSqVMm5cql7fe2FyxYQMOG&#10;DfnTn/7E0qVLqVixImPHjmXw4MF8+umndOzYkZNOOolffvmFq6++mtNOOw2Ahg0bMnDgQJ555hne&#10;ffddmjdvztKlS3niiSfYsGEDF154IRB1fXueR9OmTVm+fDnPP/88bdu2ZePGjVx88cUcddRRDBs2&#10;jI4dO9KzZ09ycnIYO3YsAFOnTuWhhx6iSpUqTJw48QDOXPwU3CIiUmDWrdtzaAP88MNGNm3adkDB&#10;3aNHD0aOHMl1111HuXLluPzyy7e/V7lyZcaMGcOMGTMoU6YMW7du3f5egwYNAKhWrRq//vor33zz&#10;Da7rAtHTwPIeElK1alVefPFFJkyYAMC2bdu2b6N27aiX4Ouvv6ZXr15A9ECSvOC+8cYbeeqpp/j1&#10;119p2bLlfh/b/tDgNBERKTDVq5fe6/tNmlSlXLkDazPOmjWLJk2a8MADD9CuXTtGjhxJ3vM2fN+n&#10;UaNG3HjjjZx66qnkfw7Hzteh69atyyeffALAxo0bWblyJQDPPvssXbt25YYbbqBZs2a73Ua9evVY&#10;tmwZwPZtbN26lenTp3PzzTfz4IMP8s477/Djjz8e0DHGQy1uEREpMFlZFahbtxwrV67f7ftXXdWI&#10;UqUOrM3oui733nsvL774Itba7aPB7777bnr06MGwYcPIycmhbNmypKens2XLlt0OHmvQoAEtW7Zk&#10;wIABVK1adfu16lNPPZXhw4fzyiuvcNhhh22/9p1/GxdccAF33XUX06ZN2/4s8PT0dMqXL89VV11F&#10;qVKlaNGiBdWrVz+gY4yHng5WBOmJQDoHoHNQ3I8fUvccBME6zj//Xb77bsP2ZcbALbecwPnnH0WZ&#10;MvF3k6fqOThYe3s6mFrcIiJSoFy3POPGdefjj9fwySe/UrlyKY47ripHHlmWEiV0hfZgKbhFRKTA&#10;1axZkpo1a9C+fY1kl3LI0a8+IiIiKUTBLSIikkIU3CIiIilEwS0iIglhrCV9wwacfJOhyMFTcIuI&#10;SIEy27ZRZvlyKt11F1VPO42q551HuYkTKfHzzwe13c2bNzN+/Pj9+sySJUtYsWLFQe23qFFwi4hI&#10;gSo7YwYVu3en9PDhpH38MRmzZlHhssuo8Pe/U+IgZhRbvXr19ulI4/X222/z008/HfA+iyLdDiYi&#10;IgWm5DffUH7AAEy+eb7zlJg8mZKzZ7P5jDMOaNsvvfQSK1eu5IUXXmDFihXbZzb761//Sv369Rk6&#10;dCirVq1i8+bNnHnmmdStW5d58+bx6aefUr9+fapVq3ZQx1ZUKLhFRKTAZOTmYtbvfrpTgNKPPMLG&#10;Tp3YWq7cfm/7ggsuYMWKFWzevJnmzZtz2mmn8e233zJ06FCGDh3K0qVLeeyxxwD44IMPyMrKomXL&#10;lnTo0OGQCW1QcIuISAEy69bt9X3nhx9wNm2CAwjuPF988QULFy5k2rRpWGtZt24dpUuXZuDAgTzw&#10;wANs2LCBTp06HfD2izoFt4iIFJhwHw/X2NqkCdsOMLQdxyEMQ+rUqUPnzp3p0KEDa9asYcKECaxe&#10;vZrc3Fxuv/12Nm/ezDnnnEOXLl0wxhCG4QHtr6hScIuISIHZkpXF1rp1SY89KnNnm666im2lSh3Q&#10;titVqsS2bdvYsGED06ZNY+zYsWzYsIFLLrmEKlWqsHr1av7yl7+QlpZGv379cByHhg0b8vTTT3P4&#10;4YdTp06dgzm0IkNPByuCiuvTcPLTOdA5KO7HD6l7DkoHARXPPx/nu++2L7PGsOGWW1h//vlsK1Mm&#10;7m2l6jk4WHo6mIiIFJqNrsu2ceMo8fHHpH3yCbZyZbYcdxx/HHkkYYkSyS4v5Sm4RUSkwG2uWZPN&#10;NWtC+/bJLuWQowlYREREUoiCW0REJIUouEVERFKIgltERCSFJHxwmud5rYB7fd9v73neccA4IDf2&#10;9nDf90cnugYREZFDRUKD2/O8fwAXAnkT1x4PPOD7/kOJ3K+IiMihKtEt7s+APsCLsdfHA1me550B&#10;fAoM9n3/9wTXICIicshI6DVu3/ffALbmW/Q+8A/f99sBXwC3JnL/IiIih5rCHpz2pu/7i2JfvwEc&#10;V8j7FxERSWmFPXPaRM/z/uL7/gKgI/BBPB+KzdlarBTHY96ZzoHOQXE/ftA5AJ2DnRV2cP8ZeMTz&#10;vM3A98CV8XyouE0wX1wn1c9P50DnoLgfP+gcQPE9B3v7ZSXhwe37/kqgTezrRcBJid6niIjIoUoT&#10;sIiIiKQQBbeIiEgKUXCLiIikEAW3iIhIClFwi4iIpBAFt4iISApRcIuIiKQQBbeIiEgKUXCLiIik&#10;EAW3iIhIClFwi4iIpBAFt4iISApRcIuIiKQQBbeIiEgKUXCLiIikEAW3iIhIClFwi4iIpBAFt4iI&#10;SApJieAOp7+D3bJlt+8ZYwq5GhERkeRJT3YB8bAvPY4d72O6nok5uTOOcSiVm0uJqVNJX7aMrdnZ&#10;bO7QgU1ZWdiMjGSXKyIikjApEdymyxnYaW9jX30KO8GnRGYDKgwbQdrWbQCUHDeOMkOHsn7YMNb3&#10;7q3wFhGRQ1ZKdJU7fS/DuXcEpvvZsGkjmz5ZwPftGrH2qJqE6dEhGGspN2gQpXJzk1ytiIhI4qRE&#10;cAOY8hVxzryISg1aU+HTVVjH8Jt7BN+d2pjfGhxOmJ6GsZYSOTnJLlVERCRhUqKrPI8xhhKfBJT8&#10;9DvKr/iB9XWrs65eddZmZbKufg3KrfyRkks/xBiDtTbZ5YqIiBS4lGlxA1hr2ZqdDYCzNaTC599z&#10;+LRlVPz4a0wYsq7B4fzMT2zzn8H+9muSqxURESl4KRXcAJs7dMDmuwXM2RZSYcWPHJ6zlEoffY0p&#10;Uw476U3CG64gHPkUdvXPSaxWRESkYKVccG/KymL9sGE7hDeAscDf/4Vz11OYC66CCpWwU8cR3ngl&#10;4YuPYX/6PjkFi4iIFKCUusYNYDMyWN+7N1tdlxI5Of9/H3f79mzKyoKMDJx23bBtO2Hfn46dMBo7&#10;YyL2vcmYE9tjevTF1MhM9mGIiIgckJQLbojCe2OjRmxs1GiPA9FMejqmbUfsiadiF7yHHe9jZ7+L&#10;nZODaXEypmdfTGadJFQvIiJy4FIyuPPb1+hxk5aGadUO2+JkWDSHcJyPnTcdO38GNG+N07Mfpnb9&#10;QqpWRETk4KR8cMfLOA4c3xaneRtYMp9w3Cj4YDbhB7OhacsowOsfnewyRURE9qrYBHceY0wU1E1a&#10;wPJFhONHwYfzCD+cB42a4fTqh2lwbLLLFBER2a1iF9x5jDGQ3RynUTMIlkYt8OWLCJcvArcxTq9+&#10;4DbW08dERKRIKbbBnccYA8c0Ie2YJtjPPvr/AA+WQoOGOD37QaNmCnARESkSin1w52caHEva327D&#10;rsglHO9HXegP3wr1jo5a4E1aKMBFRCSpFNy7YepnkfaXm7BffUE4wYeFcwgfvRNq1cfp5UGz1tFg&#10;NxERkUKm4N4LU+dI0gYMwa76Cjt+NHb+TMInhsLhtTE9PUyLkzBOWrLLFBGRYkTNxjiYzDo4V1yL&#10;c8fjmDYd4YdvsSMeILx5IOGsd7Fbtya7RBERKSYU3PvB1MjEuXQwzp1PYE7pCr/8iH3+YcKbBhBO&#10;fwe7ZUuySxQRkUOcgvsAmGo1cS4ciHP3U5gOvWDtGuxLjxP+80+E747Dbv4j2SWKiMghSsF9EEyV&#10;w3DOvRLnnqcxXc6A39dhX30qeiLZpDewf2xKdokiInKIUXAXAFOxMk7fy3DuHYHpfjb8sQk7+jnC&#10;If0JJ4zGbtyQ7BJFROQQoeAuQKZ8RZwzL8K59xlM73Mh3IZ940XCIZcT/u8V7O/rk12iiIikOAV3&#10;Apiy5XBOOzcK8D4XgpOGHftqFOCv/xe77rdklygiIilKwZ1ApnQZnB59oy70vpdCiZLYt8dEXeij&#10;n8WuWZ3sEkVEJMVoApZCYEqWwnTpgz21B3bmZOw7r2EnvYmdOh5zchdMtzMxVaolu0wREUkBCu5C&#10;ZEqUxHTshT2lK3bOu9gJY7A547EzJmLadsR0OwtTrWayyxQRkSJMwZ0EJiMDc0o3bJtO2PenYyeM&#10;xs6YiH1vMubE9my5ZCAY/dOIiMiuEn6N2/O8Vp7n5ey07DzP82Ynet9FnUlPx2nbEeeOxzD9r4Ua&#10;R2Bnv8v3A84mfPoB7Kqvkl2iiIgUMQlt1nme9w/gQmB9vmXNgMsSud9UY5w0TKt22BYnw6I5pE18&#10;gy3zpmPnz4BmrXF6epg6Rya7TBERKQIS3eL+DOiT98LzvKrAncDgBO83JRnHwRzflhqPvIzzl5ug&#10;bgNYOJvwjr+x7dE7sSs+TXaJIiKSZAltcfu+/4bneXUBPM9zgBHANcAfgEnkvlOZMQbTtCVOkxaw&#10;fBHh+FHw4TzCD+dBo2Y4vfphGhyb7DJFRCQJCnMEVHOgATAcKA009DzvQd/3rynEGlKKMQaym+M0&#10;agbBUsJxo6IgX74I3MY4vfqB2zhaT0REigVjrU3oDmIt7ld932+907KRvu+3iWMTiS2wiAvDkDAM&#10;cRwHx3H446PFrH31WTZ9EI3tK3FsUyr0u5xSx7cuEgGeV2+evLpFRGS/7faHemG1uA8qfFetWlVQ&#10;daSEzMxMVq78ltzcdUyd+i3Llq0mO7sKHTocQVZWNTIGDMFZ8Snh+FFs/nAeP98yCOodjdPTg6Yt&#10;kxLgW7ZYcnPXsXjxz5Qpk0Fu7ho++2wtTZrk1V2ejIz468rMzCx2/+47K+7noLgfP+gcQPE9B5mZ&#10;mXt8L+Et7gJgi9s/WqVKVXn22UUMGvQe+f95jIFhw06id+/a20PQfr0iuga+cA5YC7Xq4/TyoFlr&#10;TCG1dLdssYwd+zVPPvkRvXrVZejQRfuse1+K63/W/Ir7OSjuxw86B1B8z0EsuHf7A1N9mEXQggXf&#10;7hLaEOXyoEHvkZu7bvsyU7s+aQOG4Nz6CKZlO/h2JeETQwlv/Svh3GnYbdsSXm9u7joGDXqPvn2P&#10;2iW091S3iIgcGAV3ETRx4spdwi+PtZCT8+0uy01mHZwrrsW543FM247w4yrsMw8S/usqwllTsFu3&#10;JqzeqVO/5fDDy/DVV+v3u24REdk/Cu4ixhjDkiU/73WdZct+3e11bGMMTs0jcC4ZjHPnE5hTusEv&#10;P2GfH0Z40wDC6e9gt2zZYf2CqHfZstXUrBkF94HULSIi8dOE2EWMtZYmTQ5j3LiVe1wnO7syeWMT&#10;tmyxBMFaJk/+luXLV1O/fnlatKhO3brlOPKcP5Pe08NOfB07cxL2pccJx43ix+N68ubPWXz40bp8&#10;g972b/BY/nqzs6uwcOFPNGu29yec5a9bREQOzD5b3J7nNS+MQuT/de1alz01TI2B9u2PAKLQ/t//&#10;vqZbt/H8+9+Lefvtr3j88eVcdlkOkyZ9w7Rp37O1fFWcc6/EuedpbKcz2LZuHTWm/Zc+H9xJ5vKJ&#10;DLt/Hl27jmPs2K/ZsuXAQrVDhyP47rsN1KlTLq66RUTkwMXTVf5ywquQHZxwwhEMG3bSLiFoDDzy&#10;yMlkZZUHokFhgwfvfhDb0KGL+PLL9dsHhJmKlQmyz+aEiT155LNjKe1s5aaGi5ndfixXHbmcG6/J&#10;OeDBY1lZ5Rk27CRGj/6c669vts+6RUTkwMXTVb7E87zzgPfI97AQ3/dXJ6yqYq5MmZL07l0b1+1F&#10;Ts63LFtRZVXSAAAgAElEQVT2K9nZlWnffscu7alTv93rYLCvv17P/PmGRo0qbF9/9eaS3J/bhKe+&#10;OIZL6+Vyef2A692lDDjyE3JH/oa94TJM2XL7VW9GhonVW4kPP/yZRx45mU8//Y3PP//toLviRURk&#10;R/EE9+lA352WWSCt4MuRPBkZUeA2alQBY8wu14bzBoXtzddfr6ds2fTtA8Lyr//b1hL857NsRnzp&#10;cnHdT+lfL6DFD1MIh8zCtO+B6XwGpnzFg6p3d3WLiMjB2Wdw+75fqjAKkT3bXfjlDQrb2yC22rXL&#10;UaNG6e2f393667dm8Njnx/Lsl1k8d8lG2vw+C/v2a9h3x2HadcN06YOpVOWA6lVoi4gUvH0Gd+yp&#10;XtcA2cBfgb8A9/m+n/iZPWSvOnQ4YrcTnkB0Xbl27XK0aFE9rvU3helU6XcuztGXYN+bjH3ndezk&#10;t7A5EzAnd8F0OxNTZe+jxkVEJPHiGZx2P9AEaBVbvxvwUCKLkvhkZZXn4Yd3P4htyJDm1KtXfocB&#10;YXmDyPY2eMyUKInToRfOXU9iLrwKKlbG5ownvPFPhC8+hv3p+0I4MhER2ZN4rnF3JHok5we+7//m&#10;eV4XYHFiy5J4ZGQYTjutNq7bkylTovu469WrwAknVKNevXIceWS5HQaE/f8gsr0PegMwGRmYU7ph&#10;23TCvj8dO2E0dsZE7HuTMSe2x3Q/G1NTt3eJiBS2eIJ7i+/7oed5APi+/4fneYmbP1P2S0aGITu7&#10;ItnZFbcPQtvbteV9DXrbmUlPx7TtiG19Knb+e9jxPnb2u9g5OZgWJ2F6eJgj6hToMYmIyJ7FE9zL&#10;PM8bCKR5nucSXe9Wi7sI2t/BYPuzvnHSMK3aYVucDIvmEo4bhZ03AztvBjRvg9PTw9Q5cn9LFhGR&#10;/RRPcA8muqZdA5gFTAQGJbIoKbqM48DxbXCat4Yl8wnHjYKFswkXzoamLaMAr5+V7DJFRA5Z8dwO&#10;tha4vBBqkRRijImCukkLWL4oeib4h/MIP5wHxzbD6dUPc/SxyS5TROSQE8/tYNWBh4HOwBZgAnCt&#10;7/trElybpABjDGQ3x2nUDHKXRS3wjxYRfrQI3MY4PT04pomeCiYiUkDi6Sp/GlgGtCS6HWwA8CTQ&#10;L4F1SYoxxoDbmDS3Mfazj6MW+LKFhMFSOOoYnF79oFFzBbiIyEGKJ7jr+b5/er7Xf/c8b2miCpLU&#10;Zxo0JG3wrdgVn/5/F/rDt0HdBlGAN22pABcROUDxTMCyyvO8+nkvPM+rBXyXuJLkUGHqH03aX27C&#10;+dfDcHwb+OpzwsfuIrx9MHbBe9gwTHaJIiIpZ48tbs/zxhI9TKQasNjzvCnANqA9sKRwypNDgald&#10;n7QBQ7Crvoomcpk3k/DJ++Dw2pgefTEtTsak6Zk1IiLx2FtX+Zg9LB+fiELk0Gcy62D6X4vtfS72&#10;7dHYudOwzzyIHTsyCvBWp2LS47l6IyJSfO3xp6Tv+y/kf+15XpnElyPFgamRiblkMLbXOdGTyGZP&#10;wT4/DDv2VUy3szBtOyW7RBGRIiue28GuBu4CSsYWGfQ8bikA5rAamAuvwvb0sBNfx86chH15OHa8&#10;z7p+l2KbtMKUKLnvDYmIFCPx9EteA5wIfJ7gWqSYMlUOw5x7JbZHX+ykN7HTJrDmyX9DhUrR88Db&#10;dcOUKp3sMkVEioR4gvtT3/c1GE0SzlSsjOl7KbbbWZSd+y7r/vcqdsxz2HfGYDqdjmnfE1OmbLLL&#10;FBFJqniC+1HP80YBk4hmTgPA9/3/JqwqKdZM+QpUunggv7fpjH13LPbd/2HffAk76Q1Mh96YTr0x&#10;Zcvve0MiIoegeIJ7INEDRvIPTrOAglsSypQthzntXGzn07HTJkTd6ONexU55C9O+B6bzGZjyFZNd&#10;pohIoYonuOv4vn90wisR2QNTugym+9nYDr2w09/BTnojGo3+7rjo+neXPphKVZJdpohIoYhn5rQv&#10;Pc/LTHglIvtgSpbC6XIGzt1PYc69EsqWx05+i/CGKwhfeRK7+qdklygiknDxtLg3Ass8z5sP/JG3&#10;0Pf90xJWlchemBIlMR16YU/uip3zLnbCGGzOeOyMiZg2HTDdz8ZUq5nsMkVEEiKe4H4t9kekSDEZ&#10;GZhTumHbdMLOm44dPzq6F3zWlGgWth59MTWPSHaZIiIFap/BvfMMaiJFjUlPx7TpiD3xVOz897Dj&#10;feycqdi50zAtTsL08DBH1El2mSIiBSKemdPWEY0i34Hv+xUSUpHIATJOGqZVO2yLk2HRXMLxo7Dz&#10;ZmDnzYDmrXF6epg6RyW7TBGRgxJPV3l2vq9LAGcSPSVMpEgyjgPHt8Fp3hqWLIieCb5wDuHCOdCk&#10;BU6vfpj6WckuU0TkgMTTVb5yp0VDPc97H/h3YkoSKRjGGGjaAqfJCfDRYsJxo2DJfMIl8+HYZlGA&#10;H31ssssUEdkv+/0MRc/zjiGakEUkJRhjoFEznGOPg9xlUYB/tIjwo0XgNsbp6cExTaL1RESKuP29&#10;xm2IusuvS2RRIolgjAG3MWluY+xnH0dd6MsWEgZL4ahjcHr2g+zmCnARKdL29xq3Bdb4vr82QfWI&#10;FArToCFpg2/FrviUcIIPi98nHHYb1G2A08uDpq0U4CJSJO0xuD3Py7t/ZucR5ZU8z6vk+/5XiStL&#10;pHCY+keTNvCf2K9XRLeRLZxN+NjdUKte1IXevE002E1EpIjYW4t7OVFo5292WKA00VSpaQmsS6RQ&#10;mdr1MQOux676CjthNHbeTMIn74PDa2N6nI1pcQomTd/yIpJ8ewxu3/d3eG6i53kGuBH4e+yPyCHH&#10;ZNbB9L8W2/tc7NujsXOnYZ95CDv21Wgq1RPbY9L3e0yniEiBiasP0PO8I4CpQB+gle/7zyS0KpEk&#10;MzUycS4ZjHPnE5hTusHqn7AvPEJ40wDCaW9jt2zZ90ZERBJgn8Hted6ZwIfAB0Br3/dzE16VSBFh&#10;DquBc+FVOHc9henYG9auwb48nPDGKwnfHYvd/Me+NyIiUoD2NjitNPAw0BM4x/f9KYVWlUgRY6oc&#10;hjnnCmz3s7GT3sROfxv76tPYCaOj54G364YpVTrZZYpIMbC3i3ULgbpE4d3E87wm+d/0ff/BRBYm&#10;UhSZipUxfS/FdjsLO+Ut7NRx2DHPYd8Zg+l0OqZ9T0yZsskuU0QOYXsL7veBuUDN2J/8dnnoiEhx&#10;YspXwPS5ENulD/bdsdh3/4d98yXspDcwHXpjOvXGlC2/7w2JiOynvY0qv6QQ6xBJSaZsOcxp52I7&#10;n46dNiHqRh/3KnbyW5gOPTCdz8CUr5jsMkXkEJLw+1o8z2sF3Ov7fnvP844Fnoy99SnQ3/f9MNE1&#10;iCSaKV0G0/1sbIde2OnvYCe9gX37Ney746Lr3136YCpVSXaZInIISOiUUJ7n/QN4GigZW3QXMMT3&#10;/ZOJJnbpncj9ixQ2U7IUTpczcO5+CnPulVC2PHbyW4Q3XEH4yhPY1T8lu0QRSXGJbnF/RnTv94ux&#10;12f6vm89zytBdN38twTvXyQpTImSmA69sCd3xc6Zin17DDZnAnbGJEybDtFkLtV2HjoiIrJv8dzH&#10;vdDzvP6e55XZ3437vv8GsDXfaxubA30ZUJXo/nCRQ5bJyMA5pSvOHcMxlw6Gw2pgZ06KJnJ59j/Y&#10;779JdokikmKMtXsfIO55XhvgT0AX4DVguO/7y+Pdged5dYGRvu+32Wn55cDJcQyC0wh2OWTYbdvY&#10;MHMya0c9y9avvgDHocxJnSjf7zJK1GuQ7PJEpGjZ7SMK99lV7vv+bGC253mVgPOA/3metwoY5vv+&#10;6P2pwPO8t4Brfd//DFgHbIvnc6tWrdqf3aS8zMzMYnfMOzukz0FWE+w/H8RZNJdw/Cg2zJjEhhmT&#10;oHlrnJ4eps5RwCF+DuJQ3I8fdA6g+J6DzMzMPb4X1zXuWGhfCFxOdF3aBy7yPK+37/sX7Uct9wLP&#10;e573B7AB6L8fnxU5ZBjHgePb4DRvDUsWEI4fBQvnEC6cA01a4PTqB3v5jysixdc+g9vzvJeBHsA4&#10;4M++78+JLR8O/Livz/u+vxJoE/t6DnDSwRQscigxxkDTFjhNToCPFhOOGwVL5hMumc9PzU/EdjoD&#10;c/SxyS5TRIqQeFrcy4G/+b6/w30svu9v9TyvbWLKEilejDHQqBnOscdB7jLCcaPYtHAuLJwLWdlR&#10;C/yYJtF6IlKs7XNwGoDneT2ArkTXpMf6vp+T6MLyscXt+kZxvaaTn84BVF3zEz++8Dgs+yBacNQx&#10;OD37QXbzYhHg+h7QOYDiew5i17h3+x89ntvBbgEeILq2vQF40vO8QQVZoIjsquSxTUkbfAvOPx+A&#10;41rB558QDruN8K5rsYvnYkNNOihSHMXTVX4hcLzv+78BeJ73ADAbGJbIwkQkYuodTdrAf2K/XoEd&#10;72MXziZ87G6oVQ/Tw8Mc3xrjpCW7TBEpJPEE9y9Et27lWQOsT0w5IrInpnZ9zIDrsau+wk4YjZ03&#10;E/vUfdiatTA9+2JanIJJU4CLHOriCe4FwFue5z1JNAvaBcBXnuedCeD7/usJrE9EdmIy62D6X4vt&#10;fW40lercHOwzD2HHvhpNpXpie0x6wp8fJCJJEs//7rx7Ua7daflfiWY1U3CLJIGpkYm5ZBC2Vz/s&#10;O69hZ03BvvAIdtwoTLezMG07YTIykl2miBSweGZOaw/geV46YHzf35LwqkQkbuawGpgLrsL28KLH&#10;ic6YiH15OHb8KEzXMzEnd8WULLnvDYlISohnVHl1z/PeBn4HNnmeN9XzPE3pJFLEmCqH4ZxzBc49&#10;T2O69IGNG7CjRhDe0J9w4uvYTRuTXaKIFIB4nsf9KDAXqAFUB2YCwxNZlIgcOFOxMk7fS3HuGYHp&#10;0Re2bMaOeT4K8PE+dsPvyS5RRA5CPNe4s3zf9/K9vsXzvLifDiYiyWHKV8D0uRDbpQ926jjslP9h&#10;33wJO/ENTMfemE69MWXLJ7tMEdlP8bS4MzzPK5X3IvZcbj1qUyRFmLLlcHqfg3PvCMyZF0FaGnbc&#10;q4TX9yd8/QXs2jXJLlFE9kM8Le5XgSme5z0Xe30pMCZxJYlIIpjSZTDdz8Z26IWd/k40kO3t17Dv&#10;jsWc0h3TtQ+mUpVklyki+7DPFrfv+3cAzwBdgG7A88BtiS1LRBLFlCyF0+WMaBDbeX+CchWwU94i&#10;vOEKwleewK7+ad8bEZGk2WuL2/O8DKCk7/vPAc95ntcY+MT3fXWVi6Q4k1EC074n9uQu2NlTo8lc&#10;ciZgZ0zCtOkQTeZSrWayyxSRneyxxe15Xi2iR3r2yrf4JmCpbgcTOXSY9AycU7ri3DEcc+lgOKwG&#10;duYkwpsGED77EPb7b5Jdoojks7eu8vuBZ33ffzVvge/7/YCXgPsSXZiIFC6Tno7TpiPO7Y9i+l8L&#10;NWth5+QQ/msg4VP3Y79dmewSRYS9d5Vn+75/7m6W3w0sS1A9IpJkxknDtGqHbXEyLJ5LOG4Udv5M&#10;7PyZ0Lw1Tk8PU+eoZJcpUmztLbg3726h7/uh53mbElSPiBQRxnGgeRucZq1hyQLC8aNg4RzChXOg&#10;SYsowI90k12mSLGzt+Be63lefd/3V+Rf6HneUURPCRORYsAYA01b4DQ5AT5aTDhuFCyZT7hkPhx7&#10;HE7PfpisRskuU6TY2FtwPwCM9TxvEDCb6Hr4icDDRN3lIlKMGGOgUTPSGjXDBssIx70aBflHiyEr&#10;G6dXPzimSbSeiCTMHoPb9/1xnudVAEYAdWOLc4Hbfd8fWRjFiUjRZNxs0tw7sZ99TDjeh2UfED64&#10;DI46BqenB9nHK8BFEmSv93H7vv8K8IrneVWA0Pd9zY0oItuZBg1JG3wL9stPowBf/D7hsNuhboMo&#10;wJu2jK6Vi0iBiWfKU3zfX53oQkQkdZl6R5M28J/Yb1Zgx/nYhbMJH78bjqiL6dkPc3xrjJOW7DJF&#10;DglxBbeISDxMrfqYAddjv/saO2E09v0Z2Kfuw9ashenZF9PiFEyaAlzkYKgPS0QKnDm8Ns7l1+Dc&#10;+TimbSf46TvsMw8R3vxnwvcmY7duSXaJIilrny1uz/Pq7LTIAht83/8lMSWJyKHCVM/EXDII26sf&#10;9p3XsLOmYF94BDv2VUz3szBtO2MyMpJdpkhKiafFPQtYASwBFgNfAqs8z/vW87w2CaxNRA4R5rAa&#10;OBdchXPXU5iOvWHdb9iXnyC88QrCKf/D/vFHsksUSRnxBPcU4FLf9yv5vl8F8Ige7dkLeCiBtYnI&#10;IcZUOQznnCuiR4p27QMbN2BHjSC8oT/hxNexmzYmu0SRIi+e4G7q+/5/8174vv8acLzv+4uAEgmr&#10;TEQOWaZiZZyzL8W5ZwSmhwdbt2DHPE84pH80N/qG35NdokiRFU9wp3uel533IvZ1mud5pQBdnBKR&#10;A2bKV8DpcwHOvSMwp50H1mLfeplwSH9+e/EJ7O/rkl2iSJETz+1gQ4BpnuctJwr6o4HzgNuANxJY&#10;m4gUE6ZMOUzvc7CdTsNOexs7+U3WvjoC3ngZ074HpvPpmAqVkl2mSJGwzxa37/sTgCyi69n3Ag19&#10;358K3On7/s0Jrk9EihFTugxO97Nw7nmaSv2vhlKlsO+8Fl0DH/UMdo3mghKJ53YwB+gP9IitP8nz&#10;vLt931cflogkhClZivJ9zmdt87bY9yZHt5JNeQs7bQLmpM6YbmdhqlZLdpkiSRFPV/k9QFPgP0Qt&#10;9CuB+4GrE1iXiAgmowSmfU/syV2ws6di3x6DnTYBO3MSpk0HTPezMdVqJrtMkUIVT3B3A07wfX8L&#10;gOd544EPUXCLSCEx6RmYU7pi23TEzpuOnTAGO3MSdtYUTKt2mB59MTVrJbtMkUIRz6hyJy+0AXzf&#10;/wPQfIUiUuhMejpOm444tz+KueLvULMWdk4O4b8GEj51P/bblckuUSTh4mlxL/Y87yHg0djrgUSz&#10;qImIJIVx0jAtT8GecBIsnks43sfOn4mdPxOanYjTqx+mzlHJLlMkIeIJ7oHAMGA2YICJwF8TWZSI&#10;SDyM40DzNjjNWsOSBYTjR8GiuYSL5kLjE6IAP9JNdpkiBWqfwe37/lrgkvzLPM9rBOi+DBEpEowx&#10;0LQFTpMT4KPFhONGwdIFhEsXwLHH4fTsh8lqlOwyRQrEgT6Pew5QoSALERE5WMYYaNSMtEbNsMGy&#10;qAX+0WLCjxZDViOcnv2gYdNoPZEUdaDBre96ESnSjJtNmpuN/fyTqAW+7APC3H/BkS5Or36QfbwC&#10;XFLSgQa3LdAqREQSxBx1DGmDb8F++Snh+NHRYLZht0PdBjg9PWjaMrpWLpIiDjS4RURSiql3NGkD&#10;b8R+swI7fjT2g1mEj98NR9TF9OyHOb41xklLdpki+7TH4PY8bx27b1kboEzCKhIRSSBTqz7mT9dh&#10;v/saO2E09v0Z2Kfuw9asFU3k0vIUTJoCXIquvbW4s/fynohISjOH18Zcfg229znRTGxzc7DPPoQd&#10;OzKaSrV1e0y6nlwsRc8eg9v3fU1BJCKHPFM9E3PJIGyvftHDTGZNwf73Uey4UZjuZ2HadsJklEh2&#10;mSLbaUSGiAhgDquBc8FVOHc/jenYG9b9hn35CcIbrySc8hb2jz+SXaIIUAiD0zzPawXc6/t+e8/z&#10;jiOahW0r8Adwke/7PyW6BhGReJnKVTHnXIHtcTZ20pvYaW9jRz2DnTAG0+UMzKndMaU0zEeSJ6Et&#10;bs/z/gE8DZSMLfoPMND3/Q7AG8CQRO5fRORAmQqVcc6+FOeeEZgeHmzdgn3tBcIhVxCOG4Xd8Huy&#10;S5RiKtFd5Z8BffK97uf7/tLY1+nAxgTvX0TkoJjyFXD6XIBz7wjMaeeBtdi3XiYc0p/wrZexv69L&#10;dolSzCQ0uH3ff4OoWzzv9Q8Anue1IXp4yUOJ3L+ISEExZcrh9D4nCvAzL4b0dOy4UYTX9yd87QXs&#10;2jXJLlGKCWNtYidB8zyvLjDS9/02sdf9gBuA0+Mcua5Z2kSkyAk3beT3t19n7esvEq7+GVOyJGW7&#10;nUmFsy4irWq1ZJcnh4bdzslbqDOneZ53AXAlcKrv+3H/erpq1arEFVUEZWZmFrtj3pnOgc5BShx/&#10;q/bQvC3mvcnYd15j/VsjWT9+DOakzphuZ2EOMsBT4hwkWHE9B5mZmXt8r9CC2/M8B3gYWAm84Xme&#10;Bab7vn9bYdUgIlLQTEYJTPue2JO7YOfkYN8eg502ATtzEqZNhyjAqx+e7DLlEJLw4I51h7eJvaya&#10;6P2JiCSDSc/AnNwF26Yj9v3p0XSqMydhZ03BtGyH6dkXU7NWssuUQ4AeMiIiUoBMWhqmTQfsie2w&#10;C2Zhx/vRdKrvT8OccBKmp4c5om6yy5QUpuAWEUkA46RhWp6CPeGk6FGi433s/JnY+TOh2Yk4Pfth&#10;6h6V7DIlBSm4RUQSyDgONG+D06w1LF1AOG4ULJpLuGguND4Bp6eHOeqYZJcpKUTBLSJSCIwx0KQF&#10;TuMT4OPFUYAvXUC4dAE0bIrTqx8mSw9llH1TcIuIFCJjDBzbjLRjm2GDZYTjR8HHHxJ+/CFkNcLp&#10;2Q8aNo3WE9kNBbeISJIYN5s0Nxv7+SeE4/2oBZ77LzjSxenVD3t472SXKEWQHuspIpJk5qhjSBv0&#10;L5ybHoTjToQvAsJht/PD3y7CLpqLDcNklyhFiFrcIiJFhKnbgLSBN2K/WYEdP5otH8yCx++GI+pG&#10;t5Ed3wbjpCW7TEkyBbeISBFjatXH/Ok6qm39gx9eeAz7/gzsU/dja9bC9OiLaXkKJk0BXlypq1xE&#10;pIjKqFMf5/JrcO58HHNSZ/jpO+yzDxHe/GfCmZOwW7cku0RJAgW3iEgRZ6pn4lz8V5y7nsSc2h1+&#10;/Rn730cJ/zmAMGcCdsvmZJcohUjBLSKSIkzV6jjn/xnn7qcxHXvDut+wrzxBeOOVhFPewv7xR7JL&#10;lEKg4BYRSTGmclWcc67AufdpTNc+sHEDdtQzhDf0J3znNeymDckuURJIwS0ikqJMhco4Z1+Kc88I&#10;TA8Ptm7BvvYC4ZArCMeNwm74PdklSgIouEVEUpwpXwGnzwU4947AnH4eWIt962XCIf0J33wJu35t&#10;skuUAqTgFhE5RJgy5XB6nYMzdATmzIshPR073o9a4GOex65dk+wSpQAouEVEDjGmVBmc7mfh3PM0&#10;xrscSpXGTnw9ugY+agR2zS/JLlEOgiZgERE5RJmSpTCdT8ee2h373hTsO2OwU/6HnTYBc1JnTLez&#10;MFWrJ7tM2U8KbhGRQ4jjOIQ7zW1uMkpg2vfAntwZOycH+/YY7LS3sTMnYVp3wHQ/G1P98CRVvCtj&#10;DNbaZJdRZCm4RURS3MaNIUuXriEn51tyc9eQlVWJ9u2PoHHjSpQu/f9XRE16BubkLtg2HbHvT8dO&#10;GI19bzJ29ruYlu2i6VQPr5WUY9iyxZKbu46pU79l2bLVZGdXoUOHI6hUqWpS6inKTAr8VmNXrVqV&#10;7BoKVWZmJsXtmHemc6BzUNyPH+I7Bxs3hrz22pcMGTKX/D/OjYF77z2Rs86qt0N452fDbdgFs7Dj&#10;fVj1FRiDOeGkKMBr1SvAI9m7LVssY8d+zaBB7+1yDI891o4ePTLJyChezyfPzMwE2O1Ba3CaiEgK&#10;W7p0zS6hDWAtDBkyl6VL9zyS3DhpOC1PwbllGM6fb4Da9bHzZxLeNohtj92NXfl5gquP5Oau2yW0&#10;ITqGgQOnk5u7rlDqSBXqKhcRSWE5Od/uEnh5rIWcnFW0bFllr9swjgPNW+M0OxGWLiAcNwoWzyVc&#10;PBcan4DT08McdUwCqo9MnbqvY/iWRo0qJGz/qUbBLSKSohzHITd37/dm5+au2e2Atd0xxkCTFjiN&#10;T4CPF0cBvnQB4dIF0LApTq9+mKzsgip/+z6XLVu913WWLftVA9byUXCLiKSoMAzJyqrEO+98vcd1&#10;srIqxRXa+Rlj4NhmpB3bDBssIxw/Cj7+kPDjDyGrEU7PftCwabTeQbLWkp1dhXHjVu5xnezsygrt&#10;fHSNW0QkhbVvfwR7yk9joH37zIPavnGzSbvmDpwh90HjEyB3OeFD/yK89zrskvkFEqgdOuzrGI44&#10;6H0cShTcIiIprHHjStx774m7BJ8xMHRoaxo3rlQg+zFHHUPaoH/h3PQgHHcifBEQPnIH4Z3XYBfO&#10;we5nqz6/rKzyDBt20m6P4fHHTyUrq/xBVn9o0e1gRZBug9E5AJ2D4n78EP85yLuPe9q0VQRB3n3c&#10;mbvcx12Q7DcrsONHYz+YFY0gO6IupqeHOb4Nxknb7+3l3cedk/Mty5b9SnZ2Zdq3P4K2beuzphhO&#10;0bq328F0jVtEJMWVLu3QsmUVWrasEvdAtINlatXH/Ok67HffRBO5zJuOfep+bM0jMN37Ylq1+7/2&#10;7jzcquq84/h37csURFJDHpQrERIQGRUElUGQQawMFhR9cQxpFI1DTDWxFY1SH2v0aa3aBoMGB7SK&#10;8koCVBBlENGrYgIRAinWYKLRaOJQolIUwbP6xz70uV4vcEHO2Xff+/s8j4/nnmGvdy/P8XfW3vus&#10;Raioe4A3bRro0aM1PXq0/syFaC1bNucvWhvlM3SoXESkASlHaFcX2rUnOfcykuunE44dCe/8iXjv&#10;bRSuuZDCM4uJ27ft8TZzcCQ4UwpuERH5wkLbdiSTvktyw52EoaNg07vE+6dRuPo7FJY/Rtz2SdYl&#10;NhgKbhER2WdCm7YkZ11I8qMZhBEnwYfvE2fdQWHK+RSWzidu3Zp1ibmn4BYRkX0uHNCG5PTJJDfN&#10;IPz1KfDxFuLsu9M1wR//GfHjLVmXmFsKbhERKZnQ+gCSU79FctNdhDEG27cRf3YfhSsnU1jwMHHL&#10;5qxLzB0Ft4iIlFxo1Zpk/NlpgI87E4A4fxaFK8+jMO8B4uYPMq4wPxTcIiJSNqFlK5Kxp6eH0E+Z&#10;BE2aEhd6OgKfM5P4waasS6z3FNwiIlJ2oUVLklETSG6cQbBzocWXiE/8nMKUyRQenkHc1PgmXakr&#10;TTY61ygAAA44SURBVMAiIiKZCc1bEEaOIw4dRaxaSnx8DnHZo8QViwjHjmT7pIuyLrHeUXCLiEjm&#10;QtNmhGGjiYNHEp9fTlw0h/jUIt56ZjFhwHDCqFMJbdtlXWa9oOAWEZF6IzRpShh8AnHgCOILK6hY&#10;MpftVUuIzy0jHH0cYfRphHbtsy4zUwpuERGpd0JFBWHgcA46+Qz+uGAOcaETVy4nvvAUoe+gdEGT&#10;9h2zLjMTCm4REam3QkUFyVGDiX0HwZoXKCycTVxVRVxVBb37k4w1QofOWZdZVgpuERGp90KSwJED&#10;SPr0h3WrKCyYDWtWUlizEnr1IxljhE5dsy6zLBTcIiKSGyEEOPwokl79YMOaNMDXraKwbhV0O4Jk&#10;zETCYT2zLrOkFNwiIpI7IQTo3oeK7n2IL69PA3zDWgob1sKh3UnGToRuvdPnNTAKbhERybXQpScV&#10;l/ckvvIShYWejsBvnQpf75IGeK9+DSrAFdwiItIghE5dqbj0WuJrG9MAf3ElhR9fD4d0Ihlj0PuY&#10;9Fx5zim4RUSkQQkdOlNx0VXEN15Nf0a2+lkK02+EgzukvwPvN4iQVGRd5l4r+VcPMzvGzJbXuO8W&#10;Mzu/1G2LiEjjFdp3JLng70muu53Qfxi89Tpxxs0Upl5C4bkniZ9+mnWJe6WkI24zuwI4B9hc/Pur&#10;wP3AocBLpWxbREQEILRrTzj3MuJJp6dTqT7/JPHe24gLHk6nUh0wjNCkadZl1lmpR9wbgZOr/d0K&#10;mAr8R4nbFRER+YzQth3JpO+S3HAnYego2PQu8f5pFK6+gMLyx4jbPsm6xDopaXC7+1xge7W/X3X3&#10;XwIN5/I+ERHJldCmLclZF6ZLih7/N7D5A+KsOyhMOZ/CkvnErVuzLnGXcnFxWmVlZdYllF1j3Oea&#10;1Afqg8a+/6A+gBL2QWUldO/Fp9+6mA/nPsjmhY8Q/W7CEz+n1cln0WrMaSQt9ytN219AuYL7C42w&#10;33zzzX1VRy5UVlY2un2uSX2gPmjs+w/qAyhjH5x4KuHYE2Dpf1J4cgHvz5zG+4/cRzj+JMLwsYSW&#10;rUpfQzW7+rJSrh+0xd38LSIikqnQqjXJ+LNJbrqLMO5MAOL8WRSuPI/C3AeImz/IuMJUiLHeZ2hs&#10;bN849S1bfQDqg8a+/6A+gGz7IH68hfjUIuLiefDh+9C8BWHoKMIJ4wmtDyhp28URd61Hq/M/hYyI&#10;iEgJhBYtSU6cQHLjXYSJ50KLlsQn5lKYMpnCwzOIm97LpK5cXJwmIiKSldC8OeH4ccTjRhGrlhIf&#10;n0Nc9ihxxSLCsSMJJ04gtGlbtnoU3CIiInUQmjYjDBtNHDyS+PzydDKXpxYRn1lMGDCcMGoCoW3p&#10;fwWg4BYREdkDoUlTwuATiANHEH/xNPExJ1YtIT67jHDMEMJoI7RrX7L2FdwiIiJ7IVRUEAYMIx4z&#10;hLj6uXRBk5VPEV9YQeg7iDDGCO077vN2FdwiIiJfQEgqCEcNJvYdBGteoLBwNnFVFXFVFfTuTzLW&#10;CB0677P2FNwiIiL7QEgSOHIASZ/+sG4VhQWzYc1KCmtWQs++JGMnEjp1/cLtKLhFRET2oRACHH4U&#10;Sa9+sGEthYWzYf1qCutXQ7cjSMZMJBzWc6+3r+AWEREpgRACdO9NRffexJfXpyPwDWspbFgLh3Yn&#10;GTsRuvVOn7cHFNwiIiIlFrr0pOLynsRXXqKw0NND6bdOha93IRkzEQ7vV+cAV3CLiIiUSejUlYpL&#10;ryW+tjEN8BdXUph2PRzyDZIxBr37p+fKd0HBLSIiUmahQ2cqLrqK+MarxMceIa6qojD9Jji4A2H0&#10;aTD+9J2+VnOVi4iIZCS070hy/hUk191O6D8M3nqdOOPmXb5GI24REZGMhXbtCedeRjzpdOKKRbt8&#10;roJbRESknght2xFO+/Yun6ND5SIiIjmi4BYREckRBbeIiEiOKLhFRERyRMEtIiKSIwpuERGRHFFw&#10;i4iI5IiCW0REJEcU3CIiIjmi4BYREckRBbeIiEiOKLhFRERyRMEtIiKSIwpuERGRHFFwi4iI5IiC&#10;W0REJEcU3CIiIjmi4BYREckRBbeIiEiOKLhFRERyRMEtIiKSIwpuERGRHFFwi4iI5IiCW0REJEcU&#10;3CIiIjmi4BYREckRBbeIiEiOKLhFRERyRMEtIiKSIwpuERGRHFFwi4iI5IiCW0REJEealLoBMzsG&#10;uMndh5lZJ2AmUADWu/vFpW5fRESkISnpiNvMrgBmAM2Ld90CXOXuxwGJmY0rZfsiIiINTakPlW8E&#10;Tq72d193f6Z4exFwfInbFxERaVBKGtzuPhfYXu2uUO32h8CXS9m+iIhIQ1Pui9MK1W7vD/ylzO2L&#10;iIjkWskvTqvhV2Y2xN2fBkYBT9blRZWVlaWtqh5qjPtck/pAfdDY9x/UB6A+qKncwf0DYIaZNQU2&#10;AHPq8Jqw+6eIiIg0DiHGmHUNIiIiUkeagEVERCRHFNwiIiI5ouAWERHJEQW3iIhIjpT7qnKpxsya&#10;APcAHYFmwA3u/mjxsVuAl9z9p9lVWHq19QHwB+DHpJP3bAW+6e7vZFVjqe2kDzYCO/7b/xY4z90L&#10;tW6gAdjNZ+FM4BJ3H5hdhaW3k/fB68AC4OXi06a7+yOZFFgGO+mDlaRTZ/8VUEH6/4PfZ1VjfaAR&#10;d7bOBt519yGkv2ufZmZtzOwx4KRsSyub6n1wIjANuA242N2HA3OBKzOsrxxq64MbgCvdfTDpTyIb&#10;+vvhc58FADPrA3w7y8LKqLY+OBL4V3cfXvynwYZ2UW198M/AA+4+FLgG6JpdefWDRtzZcmDHBzEB&#10;tgGtgKmkb9rGoHofVJD2wUR3f7t4XxPgoywKK6PP9YG7nwJgZs2Ag4D3M6qtXD73WTCzrwD/BHyP&#10;dMTV0NX2/4O+QFczG0965OV77v6/GdVXDjX7YDswEPi1mS0Bfk/6fmjUFNwZcvctAGa2P+mb9Wp3&#10;fw14zcxGZ1pcmeykD94u3jcQuBgYkl2FpVdbHxT/PgRYSjo18NrMCiyDWvrgGuBu4HLS0yUNfiKm&#10;Wvrgh6QrK97l7i+a2VXAPwJXZFZkie3ks3A/8J67jzSza0iPwE3Nrsrs6VB5xszsa6RTv97n7rOz&#10;ricLtfWBmU0EfgKMdvf3sqyvHGrrA3f/g7t3Ae4Ebs2yvnKo3gek5/g7A9OBh4Buxes+GrQa74OH&#10;gXnu/mLx4blA78yKK5Na+uBd4NHiw4+SHoVo1DTizpCZHQg8QXo+d3nW9WShtj4ws7OB84Gh7t7g&#10;F6LZSR/MB77v7htJV9L7NMMSS24nn4Vexcc6AA+5++VZ1VcOO+mDJ8zsEndfBYwAVmdWYBnspA+q&#10;gNHAg6RH336TUXn1hoI7W1NIr5S8xsyuBSIwyt23Fm83BjX7oALoAbwGzDWzCKxw9+syrLHUansf&#10;XA3MNLOtwBbgvAzrK4ddfRYai9r64DLgNjP7BPgT6Rfahqy2PpgE3G1mF5Je63FmhvXVC5qrXERE&#10;JEd0jltERCRHFNwiIiI5ouAWERHJEQW3iIhIjii4RUREckTBLSIikiP6HbdImZlZAvwdcAbp79ab&#10;ka4Ada27f7IX27sXWOfudZpZzMxGADeT/ka2XbGGN4oP30g62UWdt7eHtR4HTHP3Xnv4ugLwVXf/&#10;nxr3fx/o6e5/uw/LFKnXFNwi5XcH8GVguLt/aGZfAmaRLqQxqdSNu/syoA+AmU0F2rj7pTseL8M8&#10;+XszecSuXqPJKKRRUXCLlJGZdSQdaR+0Y5Und//IzC4ABhZD/I/A0cXpTjGzxaTrkz9Z/Pcg0pWj&#10;5rn7D2tsvxvpsqhfIR1J/7u7z9yLUgeZ2QTgQGA9cEaxzo+B+cDhwFmks7r9W832zGw/4F7S+cYL&#10;wGp3v6C47f3N7CHS5RmbA5Pd/Vkzaw3cTjofdwF4HJhSXIc8FPevSbEPjgf+DLxNugiLSKOhc9wi&#10;5XUk8JuaSzO6+9vuPs/dPwJmApMBzKwT0IX0UPr1QHN3P4x0xDzIzP5/5TQzqyBdUekf3P0oYChw&#10;hZkdvRd1VgLDi223B04p3t8MmO/u3UhXLJuzk/ZOBlq5+5HA0cX6vlHcxsGka0z3AX5KuuIVpIH8&#10;bvEwej/gCOAHNeq6mPTLQFfgBOCQvdg3kVxTcIuUV4Hdf+6mA+cUg3gyMMPdI+kiE3cDuPs2dx/m&#10;7k9Xe10XoBNwj5m9CKwAWlA8LL6H5rn71uJodz3QttpjVXVorwroYWbLSZdhvM3df1d83SvFRTMA&#10;1lTb9onAtB37R3pKYce69DsOh48AZrn7p8UlIB/ci30TyTUdKhcpr1+QLlG5X/VRt5kdTLp85wR3&#10;/62Z/RoYT3o4ul/xadupdj7XzNqTHqreoQLYVBzl7nhOW/buUPK2arcjn10Pe/Pu2nP3T8ysM+ko&#10;fDiwzMwuAd7bxbZrfqFJgKY17qtZy/a67pBIQ6ERt0gZufubpKPEe8xsf4Bq53bfqbYa1k+AfwFW&#10;uvufi/ctBSaZWTCz5qSHqYdU2/x/Ax+b2VnF7X6NdLRcqvWLd9qemX0HmOnuS9x9CulSjT2Lrwu1&#10;bq24nGNxW81JV8JaXOM1jwPfNLPmZtYCmLiP90mk3lNwi5TfRcAG4Dkz+xXwPGngTa72nAVAK9LD&#10;5jtcRzpaXUu6LvMCd5+348Hi4eVxwHlmtpY05K529+f3sL6aV2nH2m7vpr37gcTM/svMfgnsT3oR&#10;W23b3+FS4EAzW1fcx5eAH9V4zZ2k+74eWA78ruZGRBo6LespUg+Z2UDgzj39vbOINHw6xy1Sz5jZ&#10;TOA44JyMSxGRekgjbhERkRzROW4REZEcUXCLiIjkiIJbREQkRxTcIiIiOaLgFhERyREFt4iISI78&#10;H30JlNx5+4x7AAAAAElFTkSuQmCC&#10;">
 
 
</div>
 
</div>
<div class="clear"></div>
+
<div class="sub-content">
 +
<h3>Gel Electrophoresis of Cell Lysate</h3>
 +
Because qPCR consistently gave results significantly lower than the expected copy number, an alternate means of direct copy number analysis was attempted.
  
Please refer to the <a href="https://github.com/genspace/iGEM-qPCR-Copy-Number-Analysis/blob/master/qpcr_pSB1C3_Absolute_Quantification.ipynb">Jupyter Notebook</a> for qPCR copy number analysis.
+
1 billion cells were pelleted and resuspended in 100uL of CL Buffer.  At a size of 5339bp, 20 billion copies of K909006-pSB1C3 should weigh 115ng at a concentration of 1.15ng/uL. 10uL of lysate from E. coli  was run on a 0.6% agarose gel with purified K909006-pSB1C3 at known concentrations for comparison of band brightness.
</div>
+
  
</div>
+
<img src="https://lh6.googleusercontent.com/U5GY40AdpKof5nyc_WtHxOSJ9biuVXqS5O0ygKNiJCIcNJjGNF0038wYy0UW20C4O0NtnmaNYxgQqdLvvsbKmEker5D7i-sHwPhWxI1RkVMBI2qAVxjgccLvQlNTRQNsAd4TCFzp" alt="">
<div class="content">
+
+
<h2 class="c0"><span class="c8">Conclusions</span></h2>
+
  
<p class="c0"><span>Due to time constraints, only a few qPCR runs could be completed prior to the Wiki freeze, so this data is still preliminary.</span></p>
+
Lanes were loaded in the following order (left to right)
</div>
+
E. coli Top 10 with no plasmids
 +
10ng purified K909006-pSB1C3
 +
E. coli Top 10 harboring K909006-pSB1C3
 +
50ng purified K909006-pSB1C3
 +
 
 +
The band for the plasmid in E. coli lysate was much closer in brightness to the 10ng band than the 50ng one, indicating that close to 20 copies were harbored in each lysed cell.
 +
</div>
 +
 +
<h5 class="c0"><span class="c8">Conclusions</span></h5>
 +
 
 +
<p class="c0"><span>Due to time constraints, only a few qPCR runs could be completed prior to the Wiki freeze, so this data is still preliminary.  Additional sets should be run to determine the reproducibility of these results.  Furthermore, the range of copy numbers detected for stationary phase cultures suggests that the copy number may take some time to stabilize after cell division halts.</span></p>
 +
</div>
  
 
</div>
 
</div>
 
</html>
 
</html>

Revision as of 03:57, 20 October 2016


Measurement Award

Background

The plasmid pSB1C3 is a favored vector for iGEM projects, its high copy number making it a workhorse for gene expression. However, different sources give different estimates of its copy number and no iGEM teams have independently verified these claims. Genspace developed a qPCR assay to verify plasmid copy number (PCN) in E. coli and made the first measurements of pSB1C3.

The pSB1XX plasmid series uses the pMB1 origin or replication. A point mutation in the replication primer, RNA II, allows the PCN to exceed 100 copies per cell, unless replication is repressed by the rop protein (Lin-Chao et al. 1992). Plasmids encoding the rop gene, such as pBR322, have a much lower copy number, typically closer to 18 copies per cell (Lee et al 2005). Additionally, incubation temperature has been shown to alter the copy number of plasmids using this origin of replication.

To minimize variability caused by loss of nucleic acid during purification, a lysis protocol was researched that would allow cell lysate to be used directly as the template for qPCR (Shatzkes et al 2014). A TaqMan® hydrolysis probe was designed to target the LacZ gene and LacZ (BBa_K909006) was cloned into pSB1C3. Because a copy of LacZ exists on the E. coli chromosome, lysate generated from cells without the plasmid was used as a standard, while lysate from cells with the plasmid was expected to have PCN+1 copies of the target sequence.

In addition to measuring plasmid copy number, it was decided that steady-state mRNA count would also be a valuable measurement to make. While we did not have enough time to make any mRNA measurements, the assay was designed with the intention of being usable on a DNA or RNA template. To support this flexibility, the Verso One-Step qRT-PCR kit was chosen for our assay. The Verso kit comes with an RT enhancer that degrades dsDNA during the reverse transcription step, allowing users to skip DNase treatment of samples. Used as directed, the kit works for qRT-PCR, while withholding the RT enhancer and skipping the RT stage allows the kit to function as a qPCR assay. Because samples do not require DNase treatment, both qPCR and qRT-PCR can be run using the same sample.

Video: How TaqMan Works

https://www.youtube.com/watch?v=fkUDu042xic

Sample Preparation Procedure

Bacterial cultures for testing were grown overnight to saturation, and the OD600 was measured using the following formula:

OD600 of 1.0 = 8x108 cells/mL

When necessary, 10-fold dilutions were prepared to ensure optical density remained within the linear range of our spectrophotometer.

200,000,000 cells were taken and pelleted, then resuspended in 1mL of CL Buffer for a final concentration of 1 million cells per 5 microliters. Cells were lysed at room temperature for at least 5 minutes, then frozen at -20°C. 10-fold dilutions of lysate were made using CL buffer to reduce DNA concentration to a manageable amount for qPCR. For the standard, 20,000,000,000 cells were pelleted and lysed, and 10-fold serial dilutions in CL buffer were prepared.

qPCR Procedure

Reactions were set up using the chemistry described in the kit’s manual. A master mix was created and 20uL were distributed to each reaction tube. 5uL of cell lysate (containing 105 cells for the test articles) were added to each reaction. A 3-point standard was used consisting of 105, 106, and 107 lysed E. coli cells without the plasmid. All samples were run in triplicate. The reverse transcription step was skipped and reverse transcriptase enzyme was inactivated during the 95°C hot start and qPCR continued normally using DNA as a template.

Each reaction has the following chemistry:

12.5uL Verso qRT-PCR Mix

5.45uL Molecular Biology Grade Water

5.0uL Cell lysate

1.8uL TaqMan Primer/Probe Mix

0.25uL Verso Enzyme Mix

  1. To minimize reaction variability, make a master mix first by multiplying the above volumes (withholding lysate) by the number of reactions you plan to run, with an excess of 2-3 reactions' worth.
  2. Distribute 20uL of master mix into each reaction tube. Because the edge effect impairs data quality in the outer tubes, avoid using them for anything other than a positive or negative control
  3. Distribute 5uL of the appropriate lysate (standard or test) to each reaction tube. For the negative control, use 5uL of CL Buffer.

qPCR Cycles

Run qPCR with the following cycles:

95C for 15 minutes

40 cycles of:

95C for 15 seconds

60C for 1 minute

Part 3. Plasmid Copy Measurement

A preliminary experiment was run using lysate from 1 million cells per reaction. Eight replicates were run for each sample type (with or without the reporter). After excluding outliers caused by edge effects, average CT values for six replicates for each sample were compared:

Test: 17.02

Control: 21.48

pSB1C3 absolute quantification run #1

Lysate from 1 million stationary phase cells harboring K909006-pSB1C3 was run against a 3-point standard of 106, 107, and 108 copies. Linear regression indicates approximately 18.2 copies of the target sequence for every cell in the reaction, or around 17 plasmid copies per cell.

pSB1C3 absolute quantification run #2

Lysate from 100,000 mid-log phase cells harboring K909006-pSB1C3 was compared against a 3-point standard of 105, 106, and 107 copies. Due to the reduced amplification efficiency of the 108-copy standard in run 1, cell numbers were reduced 10-fold in all subsequent experiments. Linear regression indicates approximately 13.4 copies of the target sequence for every cell in the reaction, or around 12-13 plasmid copies per cell.

Note: The K909006-pSB1C3 harboring cells used for this run were lysed in mid-log phase, which may account for the reduced PCN.

pSB1C3 absolute quantification run #3Lysate from 100,000 stationary phase cells harboring K909006-pSB1C3 was compared against a 3-point standard of 105, 106, and 107 copies. Linear regression indicates approximately 30.9 copies of the target sequence for every cell in the reaction, or around 30 plasmid copies per cell.

pSB1C3 absolute quantification run #4

Lysate from 100,000 stationary phase cells harboring K909006-pSB1C3 was compared against a 2-point standard of 105 and 106 1.1x106 copies. The 1.1x106-copy standard was created using lysate from 105 cells as well as 106 copies of purified plasmid. This point was created to test for variance in amplification efficiency of plasmid vs. genomic template. Linear regression indicates approximately 25.5 copies of the target sequence for every cell in the reaction, or around 24-25 plasmid copies per cell. Three qPCR runs using stationary phase cells and one run using mid-log phase cells indicate a PCN of around 12-13 copies during log growth, increasing to around 24 copies per cell during stationary phase.

Please refer to the Jupyter Notebook for qPCR copy number analysis.

Gel Electrophoresis of Cell Lysate

Because qPCR consistently gave results significantly lower than the expected copy number, an alternate means of direct copy number analysis was attempted. 1 billion cells were pelleted and resuspended in 100uL of CL Buffer. At a size of 5339bp, 20 billion copies of K909006-pSB1C3 should weigh 115ng at a concentration of 1.15ng/uL. 10uL of lysate from E. coli was run on a 0.6% agarose gel with purified K909006-pSB1C3 at known concentrations for comparison of band brightness. Lanes were loaded in the following order (left to right) E. coli Top 10 with no plasmids 10ng purified K909006-pSB1C3 E. coli Top 10 harboring K909006-pSB1C3 50ng purified K909006-pSB1C3 The band for the plasmid in E. coli lysate was much closer in brightness to the 10ng band than the 50ng one, indicating that close to 20 copies were harbored in each lysed cell.
Conclusions

Due to time constraints, only a few qPCR runs could be completed prior to the Wiki freeze, so this data is still preliminary. Additional sets should be run to determine the reproducibility of these results. Furthermore, the range of copy numbers detected for stationary phase cultures suggests that the copy number may take some time to stabilize after cell division halts.